Mine Countermeasures and Optimal Control

J. Town, Z. Morrison, and R. Kamalapurkar, Nonuniqueness and convergence to equivalent solutions in observer-based inverse reinforcement learning, Automatica, vol. 171, no. 111977, 2025.
URLPreprint

@Article{SCC.Town.Morrison.ea2025,
author = {Jared Town and Zachary Morrison and Rushikesh Kamalapurkar},
title = {Nonuniqueness and convergence to equivalent solutions in observer-based inverse reinforcement learning},
journal = {Automatica},
year = {2025},
volume = {171},
number = {111977},
month = January,
doi = {10.1016/j.automatica.2024.111977},
url = {https://www.sciencedirect.com/science/article/pii/S0005109824004710},
}

S. Yousaf, C. R. Bradshaw, R. Kamalapurkar, and O. San, A gray-box model for unitary air conditioners developed with symbolic regression, Int. J. Refrig., vol. 168, pp. 696-707, 2024.
URL

@Article{SCC.Yousaf.Bradshaw.ea2024b,
author = {Yousaf, Shahzad and Bradshaw, Craig R. and Kamalapurkar, Rushikesh and San, Omer},
title = {A gray-box model for unitary air conditioners developed with symbolic regression},
journal = {Int. J. Refrig.},
year = {2024},
volume = {168},
pages = {696--707},
month = December,
doi = {10.1016/j.ijrefrig.2024.10.008},
url = {https://www.sciencedirect.com/science/article/pii/S0140700724003499},
}

J. Town, Z. Morrison, and R. Kamalapurkar, Pilot performance modeling via observer-based inverse reinforcement learning, IEEE Trans. Control Syst. Technol., vol. 32, no. 6, pp. 2444-2451, 2024.
URLPreprint

@Article{SCC.Town.Morrison.ea2024,
author = {Town, Jared and Morrison, Zachary and Kamalapurkar, Rushikesh},
title = {Pilot performance modeling via observer-based inverse reinforcement learning},
journal = {IEEE Trans. Control Syst. Technol.},
year = {2024},
volume = {32},
number = {6},
pages = {2444--2451},
month = November,
doi = {10.1109/TCST.2024.3410128},
url = {https://ieeexplore.ieee.org/document/10561612},
}

S. M. N. Mahmud, M. Abudia, S. A. Nivison, Z. I. Bell, and R. Kamalapurkar, Safe adaptive output-feedback optimal control of a class of linear systems, Int. J. Robust Nonlinear Control, vol. 34, no. 11, pp. 7082-7095, 2024.
URLPreprint

@Article{SCC.Mahmud.Abudia.ea2024,
author = {Mahmud, S. M. Nahid and Abudia, Moad and Nivison, Scott A. and Bell, Zachary I. and Kamalapurkar, Rushikesh},
title = {Safe adaptive output-feedback optimal control of a class of linear systems},
journal = {Int. J. Robust Nonlinear Control},
year = {2024},
volume = {34},
number = {11},
pages = {7082--7095},
month = July,
doi = {10.1002/rnc.7334},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/rnc.7334},
}

M. Abudia, J. A. Rosenfeld, and R. Kamalapurkar, On convergent dynamic mode decomposition and its equivalence with occupation kernel regression, IFAC-PapersOnLine, 2024, to appear.
Preprint

@InProceedings{SCC.Abudia.Rosenfeld.ea2024,
author = {Abudia, Moad and Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {On convergent dynamic mode decomposition and its equivalence with occupation kernel regression},
booktitle = {IFAC-PapersOnLine},
year = {2024},
note = {to appear},
}

Z. Morrison, M. Abudia, J. Rosenfeld, and R. Kamalapurkar, Dynamic mode decomposition of control-affine nonlinear systems using discrete control Liouville operators, IEEE Control Syst. Lett., vol. 8, pp. 79-84, 2024.
URLPreprintCode

@Article{SCC.Morrison.Abudia.ea2024,
author = {Morrison, Zachary and Abudia, Moad and Rosenfeld, Joel and Kamalapurkar, Rushikesh},
title = {Dynamic mode decomposition of control-affine nonlinear systems using discrete control {L}iouville operators},
journal = {IEEE Control Syst. Lett.},
year = {2024},
volume = {8},
pages = {79--84},
doi = {10.1109/LCSYS.2023.3348205},
url = {https://ieeexplore.ieee.org/document/10376212},
}

Z. Morrison, M. Abudia, J. A. Rosenfeld, and R. Kamalapurkar, Dynamic mode decomposition of control-affine nonlinear systems using discrete control Liouville operators, Am. Control Conf., 2024, presented at the ACC, published in IEEE L-CSS.

@Conference{SCC.Morrison.Abudia.ea2024a,
author = {Morrison, Zachary and Abudia, Moad and Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {Dynamic mode decomposition of control-affine nonlinear systems using discrete control {L}iouville operators},
booktitle = {Am. Control Conf.},
year = {2024},
note = {presented at the ACC, published in IEEE L-CSS},
}

Z. Morrison, Kernel methods for system identification and fault detection in nonlinear systems, Oklahoma State University, 2024.
URLPreprint

@MastersThesis{SCC.Morrison2024,
author = {Morrison, Zachary},
title = {Kernel methods for system identification and fault detection in nonlinear systems},
institution = {Oklahoma State University},
year = {2024},
url = {https://hdl.handle.net/20.500.14446/344973},
}

T. E. Ogri, M. Qureshi, Z. I. Bell, K. Waters, and R. Kamalapurkar, An adaptive optimal control approach to monocular depth observability maximization, Proc. Am. Control Conf., 2024.

@InProceedings{SCC.Ogri.Qureshi.ea2024,
author = {Ogri, Tochukwu Elijah and Qureshi, Muzaffar and Bell, Zachary I. and Waters, Kristy and Kamalapurkar, Rushikesh},
title = {An adaptive optimal control approach to monocular depth observability maximization},
booktitle = {Proc. Am. Control Conf.},
year = {2024},
}

J. A. Rosenfeld, B. Russo, R. Kamalapurkar, and T. Johnson, The occupation kernel method for nonlinear system identification, SIAM J. Control Optim., vol. 62, no. 3, pp. 1643-1668, 2024.
URLPreprint

@Article{SCC.Rosenfeld.Russo.ea2024,
author = {Rosenfeld, Joel A. and Russo, Benjamin and Kamalapurkar, Rushikesh and Johnson, Taylor},
title = {The occupation kernel method for nonlinear system identification},
journal = {SIAM J. Control Optim.},
year = {2024},
volume = {62},
number = {3},
pages = {1643--1668},
doi = {10.1137/19M127029X},
url = {https://epubs.siam.org/doi/full/10.1137/19M127029X},
}

J. A. Rosenfeld, B. Russo, and R. Kamalapurkar, Operator approximations for inverse problems, Int. Symp. Math. Theory Netw. Syst., 2024.
Preprint

@Conference{SCC.Rosenfeld.Russo.ea2024a,
author = {Rosenfeld, Joel A. and Russo, Benjamin and Kamalapurkar, Rushikesh},
title = {Operator approximations for inverse problems},
booktitle = {Int. Symp. Math. Theory Netw. Syst.},
year = {2024},
}

S. Yousaf, C. R. Bradshaw, R. Kamalapurkar, and O. San, Quantification of predictive capabilities of an empirical model for a variable speed heat pump system trained with sparse data, Purdue Herrick Conf., 2024.

@Conference{SCC.Yousaf.Bradshaw.ea2024,
author = {Yousaf, Shahzad and Bradshaw, Craig R. and Kamalapurkar, Rushikesh and San, Omer},
title = {Quantification of predictive capabilities of an empirical model for a variable speed heat pump system trained with sparse data},
booktitle = {Purdue Herrick Conf.},
year = {2024},
}

S. Yousaf, C. R. Bradshaw, R. Kamalapurkar, and O. San, Reduced data dependency in heat pump performance prediction through gray-box modeling, Purdue Herrick Conf., 2024.

@Conference{SCC.Yousaf.Bradshaw.ea2024a,
author = {Yousaf, Shahzad and Bradshaw, Craig R. and Kamalapurkar, Rushikesh and San, Omer},
title = {Reduced data dependency in heat pump performance prediction through gray-box modeling},
booktitle = {Purdue Herrick Conf.},
year = {2024},
}

T. E. Ogri, Z. I. Bell, and R. Kamalapurkar, State and parameter estimation for affine nonlinear systems, Proc. IEEE Conf. Decis. Control, pp. 1517-1522, 2023.
URLPreprint

@InProceedings{SCC.Ogri.Bell.ea2023,
author = {Ogri, Tochukwu Elijah and Bell, Zachary I. and Kamalapurkar, Rushikesh},
title = {State and parameter estimation for affine nonlinear systems},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Singapore},
year = {2023},
pages = {1517--1522},
month = December,
doi = {10.1109/CDC49753.2023.10383293},
url = {https://ieeexplore.ieee.org/document/10383293},
}

J. A. Rosenfeld, and R. Kamalapurkar, Convergent dynamic mode decomposition, Proc. IEEE Conf. Decis. Control, pp. 4972-4977, 2023.
URLPreprint

@InProceedings{SCC.Rosenfeld.Kamalapurkar2023,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {Convergent dynamic mode decomposition},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Singapore},
year = {2023},
pages = {4972--4977},
month = December,
doi = {10.1109/CDC49753.2023.10383684},
url = {https://ieeexplore.ieee.org/document/10383684},
}

T. E. Ogri, S. M. N. Mahmud, Z. I. Bell, and R. Kamalapurkar, Output feedback adaptive optimal control of affine nonlinear systems with a linear measurement model, Proc. IEEE Conf. Control Technol. Appl., pp. 645-650, 2023.
URLPreprint

@InProceedings{SCC.Ogri.Mahmud.ea2023,
author = {Ogri, Tochukwu Elijah and Mahmud, S. M. Nahid and Bell, Zachary I. and Kamalapurkar, Rushilesh},
title = {Output feedback adaptive optimal control of affine nonlinear systems with a linear measurement model},
booktitle = {Proc. IEEE Conf. Control Technol. Appl.},
year = {2023},
pages = {645--650},
month = August,
doi = {10.1109/CCTA54093.2023.10252924},
url = {https://ieeexplore.ieee.org/document/10252924},
}

J. A. Rosenfeld, and R. Kamalapurkar, Singular dynamic mode decomposition, SIAM J. Appl. Dyn. Syst., vol. 22, no. 3, pp. 2357-2381, 2023.
URLPreprintCode

@Article{SCC.Rosenfeld.Kamalapurkar2023a,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {Singular dynamic mode decomposition},
journal = {SIAM J. Appl. Dyn. Syst.},
howpublished = {{arXiv:2106.02639}},
year = {2023},
volume = {22},
number = {3},
pages = {2357--2381},
month = August,
doi = {10.1137/22M1475892},
url = {https://epubs.siam.org/doi/10.1137/22M1475892},
}

W. Makumi, M. L. Greene, Z. I. Bell, S. Nivison, R. Kamalapurkar, and W. E. Dixon, Hierarchical reinforcement learning-based supervisory control of unknown nonlinear systems, IFAC-PapersOnLine, vol. 56, no. 2, pp. 6871-6876, 2023.
URLPreprint

@InProceedings{SCC.Makumi.Greene.ea2023a,
author = {Makumi, Waijiku and Greene, Max L. and Bell, Zachary I. and Nivison, Scott and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Hierarchical reinforcement learning-based supervisory control of unknown nonlinear systems},
booktitle = {IFAC-PapersOnLine},
year = {2023},
volume = {56},
number = {2},
pages = {6871--6876},
month = July,
doi = {https://doi.org/10.1016/j.ifacol.2023.10.485},
url = {https://www.sciencedirect.com/science/article/pii/S2405896323008522},
}

J. Town, Z. Morrison, and R. Kamalapurkar, Nonuniqueness and convergence to equivalent solutions in observer-based inverse reinforcement learning, Proc. Am. Control Conf., pp. 3989-3994, 2023.
URLPreprint

@InProceedings{SCC.Town.Morrison.ea2023,
author = {Town, Jared and Morrison, Zachary and Kamalapurkar, Rushikesh},
title = {Nonuniqueness and convergence to equivalent solutions in observer-based inverse reinforcement learning},
booktitle = {Proc. Am. Control Conf.},
year = {2023},
pages = {3989--3994},
month = July,
doi = {10.23919/ACC55779.2023.10156188},
url = {https://ieeexplore.ieee.org/abstract/document/10156188},
}

S. Yousaf, C. R. Bradshaw, R. Kamalapurkar, and O. San, Investigating critical model input features for unitary air conditioning equipment, Energy Build., vol. 284, no. 112823, pp. 1-12, 2023.
URLPreprint

@Article{SCC.Yousaf.Bradshaw.ea2023,
author = {Yousaf, Shahzad and Bradshaw, Craig R. and Kamalapurkar, Rushikesh and San, Omer},
title = {Investigating critical model input features for unitary air conditioning equipment},
journal = {Energy Build.},
year = {2023},
volume = {284},
number = {112823},
pages = {1--12},
month = April,
doi = {10.1016/j.enbuild.2023.112823},
url = {https://www.sciencedirect.com/science/article/pii/S0378778823000531},
}

W. Makumi, M. Greene, Z. I. Bell, B. Bialy, R. Kamalapurkar, and W. E. Dixon, Hierarchical reinforcement learning and gain scheduling-based control of a hypersonic vehicle, AIAA SciTech Forum, 2023.
URLPreprint

@InProceedings{SCC.Makumi.Greene.ea2023,
author = {Makumi, Waijiku and Greene, Max and Bell, Zachary I. and Bialy, Brendan and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Hierarchical reinforcement learning and gain scheduling-based control of a hypersonic vehicle},
booktitle = {AIAA SciTech Forum},
year = {2023},
month = January,
doi = {10.2514/6.2023-2505},
url = {https://arc.aiaa.org/doi/abs/10.2514/6.2023-2505},
}

M. Abudia, J. A. Rosenfeld, and R. Kamalapurkar, Carleman lifting for nonlinear system identification with guaranteed error bounds, Proc. Am. Control Conf., pp. 929-934, 2023.
URLPreprint

@InProceedings{SCC.Abudia.Rosenfeld.ea2023,
author = {Abudia, Moad and Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {Carleman lifting for nonlinear system identification with guaranteed error bounds},
booktitle = {Proc. Am. Control Conf.},
year = {2023},
pages = {929--934},
doi = {10.23919/ACC55779.2023.10155924},
url = {https://ieeexplore.ieee.org/document/10155924},
}

E. Gonzalez, L. Avazpour, R. Kamalapurkar, and J. A. Rosenfeld, Modeling partially unknown dynamics with continuous time DMD, Proc. Am. Control Conf., pp. 2913-2918, 2023.
URLPreprint

@InProceedings{SCC.Gonzalez.Avazpour.ea2023,
author = {Gonzalez, Efrain and Avazpour, Ladan and Kamalapurkar, Rushikesh and Rosenfeld, Joel A.},
title = {Modeling partially unknown dynamics with continuous time {DMD}},
booktitle = {Proc. Am. Control Conf.},
year = {2023},
pages = {2913--2918},
doi = {10.23919/ACC55779.2023.10156424},
url = {https://ieeexplore.ieee.org/document/10156424},
}

Z. Morrison, B. P. Russo, Y. Lian, and R. Kamalapurkar, Fault detection via occupation kernel principal component analysis, IEEE Control Syst. Lett., vol. 7, pp. 2695-2700, 2023.
URLPreprintCode

@Article{SCC.Morrison.Russo.ea2023,
author = {Morrison, Zachary and Russo, Benjamin P. and Lian, Yingzhao and Kamalapurkar, Rushikesh},
title = {Fault detection via occupation kernel principal component analysis},
journal = {IEEE Control Syst. Lett.},
year = {2023},
volume = {7},
pages = {2695--2700},
doi = {10.1109/LCSYS.2023.3287568},
url = {https://ieeexplore.ieee.org/document/10158360},
}

Z. Morrison, B. P. Russo, Y. Lian, and R. Kamalapurkar, Fault detection via occupation kernel principal component analysis, IEEE Conf. Decis. Control, 2023, presented at IEEE CDC, published in IEEE L-CSS.
Preprint

@Conference{SCC.Morrison.Russo.ea2023a,
author = {Morrison, Zachary and Russo, Benjamin P. and Lian, Yingzhao and Kamalapurkar, Rushikesh},
title = {Fault detection via occupation kernel principal component analysis},
booktitle = {IEEE Conf. Decis. Control},
year = {2023},
note = {presented at IEEE CDC, published in IEEE L-CSS},
}

J. Town, Nonuniqueness and equivalence in online inverse reinforcement learning with applications to pilot performance modeling, Oklahoma State University, 2023.
URLPreprint

@MastersThesis{SCC.Town2023,
author = {Town, Jared},
title = {Nonuniqueness and equivalence in online inverse reinforcement learning with applications to pilot performance modeling},
institution = {Oklahoma State University},
year = {2023},
url = {https://www.proquest.com/docview/2847213758},
}

R. V. Self, M. Abudia, S. M. N. Mahmud, and R. Kamalapurkar, Model-based inverse reinforcement learning for deterministic systems, Automatica, vol. 140, no. 110242, pp. 1-13, 2022.
URLPreprintCode

@Article{SCC.Self.Abudia.ea2022,
author = {Self, Ryan V. and Abudia, Moad and Mahmud, S M Nahid and Kamalapurkar, Rushikesh},
title = {Model-based inverse reinforcement learning for deterministic systems},
journal = {Automatica},
year = {2022},
volume = {140},
number = {110242},
pages = {1--13},
month = June,
doi = {10.1016/j.automatica.2022.110242},
url = {https://www.sciencedirect.com/science/article/pii/S0005109822000875},
}

J. A. Rosenfeld, R. Kamalapurkar, L. F. Gruss, and T. T. Johnson, Dynamic mode decomposition for continuous time systems with the Liouville operator, J. Nonlinear Sci., vol. 32, no. 1, pp. 1-30, 2022.
URLPreprintCode

@Article{SCC.Rosenfeld.Kamalapurkar.ea2022,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Gruss, L. Forest and Johnson, Taylor T.},
title = {Dynamic mode decomposition for continuous time systems with the {L}iouville operator},
journal = {J. Nonlinear Sci.},
year = {2022},
volume = {32},
number = {1},
pages = {1--30},
month = February,
doi = {10.1007/s00332-021-09746-w},
url = {https://link.springer.com/article/10.1007/s00332-021-09746-w},
}

R. Kamalapurkar, and J. A. Rosenfeld, An occupation kernel approach to optimal control, Int. Symp. Math. Theory Netw. Syst., 2022, abstract-reviewed talk.

@Conference{SCC.Kamalapurkar.Rosenfeld2022,
author = {Kamalapurkar, Rushikesh and Rosenfeld, Joel A.},
title = {An occupation kernel approach to optimal control},
booktitle = {Int. Symp. Math. Theory Netw. Syst.},
year = {2022},
note = {abstract-reviewed talk},
}

J. A. Rosenfeld, R. Kamalapurkar, and B. P. Russo, Theoretical foundations for the dynamic mode decomposition of high order dynamical systems, Int. Symp. Math. Theory Netw. Syst., 2022, abstract-reviewed talk.

@Conference{SCC.Rosenfeld.Kamalapurkar.ea2022a,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Russo, Benjamin P.},
title = {Theoretical foundations for the dynamic mode decomposition of high order dynamical systems},
booktitle = {Int. Symp. Math. Theory Netw. Syst.},
year = {2022},
note = {abstract-reviewed talk},
}

B. P. Russo, R. Kamalapurkar, D. Chang, and J. A. Rosenfeld, Motion tomography via occupation kernels, J. Comput. Dyn., vol. 9, no. 1, pp. 27-45, 2022.
URLPreprintCode

@Article{SCC.Russo.Kamalapurkar.ea2022,
author = {Russo, Benjamin P. and Kamalapurkar, Rushikesh and Chang, Dongsik and Rosenfeld, Joel A.},
title = {Motion tomography via occupation kernels},
journal = {J. Comput. Dyn.},
year = {2022},
volume = {9},
number = {1},
pages = {27--45},
doi = {10.3934/jcd.2021026},
url = {https://www.aimsciences.org/article/doi/10.3934/jcd.2021026},
}

S. Yousaf, C. R. Bradshaw, R. Kamalapurkar, and O. San, Physics informed machine learning based reduced order model of unitary equipment, Purdue Herrick Conf., 2022, abstract-reviewed talk.

@Conference{SCC.Yousaf.Bradshaw.ea2022,
author = {Yousaf, Shahzad and Bradshaw, Craig R. and Kamalapurkar, Rushikesh and San, Omer},
title = {Physics informed machine learning based reduced order model of unitary equipment},
booktitle = {Purdue Herrick Conf.},
year = {2022},
note = {abstract-reviewed talk},
}

S. M. N. Mahmud, S. A. Nivison, Z. I. Bell, and R. Kamalapurkar, Safe model-based reinforcement learning for systems with parametric uncertainties, Front. Robot. AI, vol. 8, no. 733104, pp. 1-13, 2021.
URLPreprintCorrigendumCode

@Article{SCC.Mahmud.Nivison.ea2021,
author = {Mahmud, S M Nahid and Nivison, Scott A. and Bell, Zachary I. and Kamalapurkar, Rushikesh},
title = {Safe model-based reinforcement learning for systems with parametric uncertainties},
journal = {Front. Robot. AI},
year = {2021},
volume = {8},
number = {733104},
pages = {1--13},
month = December,
doi = {10.3389/frobt.2021.733104},
url = {https://www.frontiersin.org/articles/10.3389/frobt.2021.733104},
}

R. V. Self, K. Coleman, H. Bai, and R. Kamalapurkar, Online observer-based inverse reinforcement learning, IEEE Control Syst. Lett., vol. 5, no. 6, pp. 1922-1927, 2021.
URLPreprintCorrigendum

@Article{SCC.Self.Coleman.ea2021a,
author = {Self, Ryan V. and Coleman, Kevin and Bai, He and Kamalapurkar, Rushikesh},
title = {Online observer-based inverse reinforcement learning},
journal = {IEEE Control Syst. Lett.},
year = {2021},
volume = {5},
number = {6},
pages = {1922--1927},
month = December,
doi = {10.1109/LCSYS.2020.3046527},
url = {https://ieeexplore.ieee.org/document/9302679},
}

G. Rotithor, D. Trombetta, R. Kamalapurkar, and A. P. Dani, Full and reduced order observers for image-based depth estimation using concurrent learning, IEEE Trans. Control Syst. Technol., vol. 29, no. 6, pp. 2647-2653, 2021.
URLPreprint

@Article{SCC.Rotithor.Trombetta.ea2021,
author = {Rotithor, Ghananeel and Trombetta, Daniel and Kamalapurkar, Rushikesh and Dani, Ashwin P.},
title = {Full and reduced order observers for image-based depth estimation using concurrent learning},
journal = {IEEE Trans. Control Syst. Technol.},
year = {2021},
volume = {29},
number = {6},
pages = {2647--2653},
month = November,
doi = {10.1109/TCST.2020.3036369},
url = {https://ieeexplore.ieee.org/document/9270583},
}

J. A. Rosenfeld, and R. Kamalapurkar, Dynamic mode decomposition with control Liouville operators, IFAC-PapersOnLine, vol. 54, no. 9, pp. 707-712, 2021.
URLPreprint

@InProceedings{SCC.Rosenfeld.Kamalapurkar2021,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {Dynamic mode decomposition with control {L}iouville operators},
booktitle = {IFAC-PapersOnLine},
year = {2021},
volume = {54},
number = {9},
pages = {707--712},
month = July,
doi = {10.1016/j.ifacol.2021.06.133},
url = {https://www.sciencedirect.com/science/article/pii/S2405896321006182},
}

S. M. N. Mahmud, K. Hareland, S. Nivison, Z. I. Bell, and R. Kamalapurkar, A safety aware model-based reinforcement learning framework for systems with uncertainties, Proc. Am. Control Conf., pp. 1979-1984, 2021.
URLPreprint

@InProceedings{SCC.Mahmud.Hareland.ea2021,
author = {Mahmud, S M Nahid and Hareland, Katrine and Nivison, Scott and Bell, Zachary I. and Kamalapurkar, Rushikesh},
title = {A safety aware model-based reinforcement learning framework for systems with uncertainties},
booktitle = {Proc. Am. Control Conf.},
address = {New Orleans, LA, USA},
year = {2021},
pages = {1979--1984},
month = May,
doi = {10.23919/ACC50511.2021.9482976},
url = {https://ieeexplore.ieee.org/document/9482976},
}

J. A. Rosenfeld, R. Kamalapurkar, L. F. Gruss, and T. T. Johnson, On occupation kernels, Liouville operators, and dynamic mode decomposition, Proc. Am. Control Conf., pp. 3957-3962, 2021.
URLPreprint

@InProceedings{SCC.Rosenfeld.Kamalapurkar.ea2021,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Gruss, L. Forest and Johnson, Taylor T.},
title = {On occupation kernels, {L}iouville operators, and dynamic mode decomposition},
booktitle = {Proc. Am. Control Conf.},
address = {New Orleans, LA, USA},
year = {2021},
pages = {3957--3962},
month = May,
doi = {10.23919/ACC50511.2021.9483121},
url = {https://ieeexplore.ieee.org/document/9483121},
}

R. V. Self, K. Coleman, H. Bai, and R. Kamalapurkar, Online observer-based inverse reinforcement learning, Proc. Am. Control Conf., pp. 1959-1964, 2021.
URLPreprint

@InProceedings{SCC.Self.Coleman.ea2021,
author = {Self, Ryan V. and Coleman, Kevin and Bai, He and Kamalapurkar, Rushikesh},
title = {Online observer-based inverse reinforcement learning},
booktitle = {Proc. Am. Control Conf.},
address = {New Orleans, LA, USA},
year = {2021},
pages = {1959--1964},
month = May,
doi = {10.23919/ACC50511.2021.9482906},
url = {https://ieeexplore.ieee.org/document/9482906},
}

M. L. Greene, P. Deptula, R. Kamalapurkar, and W. E. Dixon, Mixed density methods for approximate dynamic programming, Handbook of Reinforcement Learning and Control, ser. Studies in Systems, Decision and Control, vol. 325, Kyriakos G. Vamvoudakis, Yan Wan, Frank Lewis, and Derya Cansever (Eds.), Springer International Publishing, pp. 139-172, 2021.
URLPreprint

@InCollection{SCC.Greene.Deptula.ea2021,
author = {Greene, Max L. and Deptula, Patryk and Kamalapurkar, Rushikesh and Dixon, Warren E.},
editor = {Vamvoudakis, Kyriakos G. and Wan, Yan and Lewis, Frank and Cansever, Derya},
title = {Mixed density methods for approximate dynamic programming},
booktitle = {Handbook of Reinforcement Learning and Control},
publisher = {Springer International Publishing},
series = {Studies in Systems, Decision and Control},
address = {Cham},
year = {2021},
volume = {325},
pages = {139--172},
doi = {10.1007/978-3-030-60990-0_5},
url = {https://link.springer.com/chapter/10.1007/978-3-030-60990-0_5},
}

K. Hareland, Impact of vibration and stochastic resonance electrical stimulation on muscle contraction, Oklahoma State University, 2021.
URLPreprint

@MastersThesis{SCC.Hareland2021,
author = {Katrine Hareland},
title = {Impact of vibration and stochastic resonance electrical stimulation on muscle contraction},
institution = {Oklahoma State University},
year = {2021},
url = {https://www.proquest.com/docview/2585472004},
}

S. M. N. Mahmud, Safety-aware model-based reinforcement learning using barrier transformation, Oklahoma State University, 2021.
URLPreprint

@MastersThesis{SCC.Mahmud2021,
author = {S M Nahid Mahmud},
title = {Safety-aware model-based reinforcement learning using barrier transformation},
institution = {Oklahoma State University},
year = {2021},
url = {https://www.proquest.com/docview/2585443288},
}

M. Abudia, M. Harlan, R. V. Self, and R. Kamalapurkar, Switched optimal control and dwell time constraints: a preliminary study, Proc. IEEE Conf. Decis. Control, pp. 3261-3266, 2020.
URLPreprint

@InProceedings{SCC.Abudia.Harlan.ea2020,
author = {Abudia, Moad and Harlan, Michael and Self, Ryan V. and Kamalapurkar, Rushikesh},
title = {Switched optimal control and dwell time constraints: a preliminary study},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Jeju Island, Republic of Korea},
year = {2020},
pages = {3261--3266},
month = December,
doi = {10.1109/CDC42340.2020.9304087},
url = {https://ieeexplore.ieee.org/document/9304087},
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M. L. Greene, M. Abudia, R. Kamalapurkar, and W. E. Dixon, Model-based reinforcement learning for optimal feedback control of switched systems, Proc. IEEE Conf. Decis. Control, pp. 162-167, 2020.
URLPreprint

@InProceedings{SCC.Greene.Abudia.ea2020,
author = {Greene, Max L. and Abudia, Moad and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Model-based reinforcement learning for optimal feedback control of switched systems},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Jeju Island, Republic of Korea},
year = {2020},
pages = {162--167},
month = December,
doi = {10.1109/CDC42340.2020.9304400},
url = {https://ieeexplore.ieee.org/document/9304400},
}

R. V. Self, S. M. N. Mahmud, K. Hareland, and R. Kamalapurkar, Online inverse reinforcement learning with limited data, Proc. IEEE Conf. Decis. Control, pp. 603-608, 2020.
URLPreprint

@InProceedings{SCC.Self.Mahmud.ea2020,
author = {Self, Ryan V. and Mahmud, S M Nahid and Hareland, Katrine and Kamalapurkar, Rushikesh},
title = {Online inverse reinforcement learning with limited data},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Jeju Island, Republic of Korea},
year = {2020},
pages = {603--608},
month = December,
doi = {10.1109/CDC42340.2020.9303883},
url = {https://ieeexplore.ieee.org/document/9303883},
}

K. Hareland, J. Hausselle, and R. Kamalapurkar, Quantification of the effects of vibration on muscle contraction, Int. Virtual Mechatron. Conf. Worksh., 2020, (abstract-reviewed talk).

@Conference{SCC.Hareland.Hausselle.ea2020,
author = {Hareland, Katrine and Hausselle, Jerome and Kamalapurkar, Rushikesh},
title = {Quantification of the effects of vibration on muscle contraction},
booktitle = {Int. Virtual Mechatron. Conf. Worksh.},
address = {Stillwater, OK, USA},
year = {2020},
month = October,
note = {(abstract-reviewed talk)},
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R. V. Self, M. Abudia, and R. Kamalapurkar, Online inverse reinforcement learning for systems with disturbances, Proc. Am. Control Conf., pp. 1118-1123, 2020.
URLPreprint

@InProceedings{SCC.Self.Abudia.ea2020,
author = {Self, Ryan V. and Abudia, Moad and Kamalapurkar, Rushikesh},
title = {Online inverse reinforcement learning for systems with disturbances},
booktitle = {Proc. Am. Control Conf.},
year = {2020},
pages = {1118--1123},
month = July,
doi = {10.23919/ACC45564.2020.9147344},
url = {https://ieeexplore.ieee.org/document/9147344},
}

R. Kamalapurkar, W. E. Dixon, and A. R. Teel, On reduction of differential inclusions and Lyapunov stability, ESAIM Control Optim. Calc. Var., vol. 26, 2020.
URLPreprint

@Article{SCC.Kamalapurkar.Dixon.ea2020,
author = {Rushikesh Kamalapurkar and Warren E. Dixon and Andrew R. Teel},
title = {On reduction of differential inclusions and {L}yapunov stability},
journal = {ESAIM Control Optim. Calc. Var.},
year = {2020},
volume = {26},
month = March,
doi = {10.1051/cocv/2019074},
url = {https://www.esaim-cocv.org/10.1051/cocv/2019074},
}

R. V. Self, On model-based online inverse reinforcement learning, Oklahoma State University, 2020.
URLPreprint

@PhdThesis{SCC.Self2020,
author = {Self, Ryan V.},
title = {On model-based online inverse reinforcement learning},
institution = {Oklahoma State University},
year = {2020},
url = {https://hdl.handle.net/11244/329936},
}

A. Parikh, R. Kamalapurkar, and W. E. Dixon, Integral concurrent learning: adaptive control with parameter convergence using finite excitation, Int. J. Adapt. Control Signal Process., vol. 33, no. 12, pp. 1775-1787, 2019.
URLPreprintCode

@Article{SCC.Parikh.Kamalapurkar.ea2019,
author = {Parikh, Anup and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Integral concurrent learning: adaptive control with parameter convergence using finite excitation},
journal = {Int. J. Adapt. Control Signal Process.},
year = {2019},
volume = {33},
number = {12},
pages = {1775--1787},
month = December,
doi = {10.1002/acs.2945},
url = {https://onlinelibrary.wiley.com/doi/full/10.1002/acs.2945},
}

J. A. Rosenfeld, R. Kamalapurkar, B. Russo, and T. T. Johnson, Occupation kernels and densely defined Liouville operators for system identification, Proc. IEEE Conf. Decis. Control, pp. 6455-6460, 2019.
URLPreprint

@InProceedings{SCC.Rosenfeld.Kamalapurkar.ea2019a,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Russo, Benjamin and Johnson, Taylor T.},
title = {Occupation kernels and densely defined {L}iouville operators for system identification},
booktitle = {Proc. IEEE Conf. Decis. Control},
year = {2019},
pages = {6455--6460},
month = December,
doi = {10.1109/CDC40024.2019.9029337},
url = {https://ieeexplore.ieee.org/document/9029337},
}

G. Rotithor, D. Trombetta, R. Kamalapurkar, and A. P. Dani, Reduced order observer for structure from motion using concurrent learning, Proc. IEEE Conf. Decis. Control, pp. 6815-6820, 2019.
URLPreprint

@InProceedings{SCC.Rotithor.Trombetta.ea2019,
author = {Rotithor, Ghananeel and Trombetta, Daniel and Kamalapurkar, Rushikesh and Dani, Ashwin P.},
title = {Reduced order observer for structure from motion using concurrent learning},
booktitle = {Proc. IEEE Conf. Decis. Control},
year = {2019},
pages = {6815--6820},
month = December,
doi = {10.1109/CDC40024.2019.9029636},
url = {https://ieeexplore.ieee.org/document/9029636},
}

S. Thapa, R. V. Self, R. Kamalapurkar, and H. Bai, Cooperative manipulation of an unknown payload with concurrent mass and drag force estimation, Proc. IEEE Conf. Decis. Control, pp. 2880-2885, 2019.
URLPreprint

@InProceedings{SCC.Thapa.Self.ea2019a,
author = {Thapa, Sandesh and Self, Ryan V. and Kamalapurkar, Rushikesh and Bai, He},
title = {Cooperative manipulation of an unknown payload with concurrent mass and drag force estimation},
booktitle = {Proc. IEEE Conf. Decis. Control},
year = {2019},
pages = {2880--2885},
month = December,
url = {https://css.paperplaza.net/conferences/conferences/CDC19/program/CDC19_ContentListWeb_2.html#tha03_01},
}

S. Thapa, R. V. Self, R. Kamalapurkar, and H. Bai, Cooperative manipulation of an unknown payload with concurrent mass and drag force estimation, IEEE Control Syst. Lett., vol. 3, no. 4, pp. 907-912, 2019.
URLPreprint

@Article{SCC.Thapa.Self.ea2019,
author = {Thapa, Sandesh and Self, Ryan V. and Kamalapurkar, Rushikesh and Bai, He},
title = {Cooperative manipulation of an unknown payload with concurrent mass and drag force estimation},
journal = {IEEE Control Syst. Lett.},
year = {2019},
volume = {3},
number = {4},
pages = {907--912},
month = October,
doi = {10.1109/LCSYS.2019.2919841},
url = {https://ieeexplore.ieee.org/document/8725526},
}

R. V. Self, M. Harlan, and R. Kamalapurkar, Online inverse reinforcement learning for nonlinear systems, Proc. IEEE Conf. Control Technol. Appl., pp. 296-301, 2019.
URLPreprint

@InProceedings{SCC.Self.Harlan.ea2019a,
author = {Self, Ryan V. and Harlan, Michael and Kamalapurkar, Rushikesh},
title = {Online inverse reinforcement learning for nonlinear systems},
booktitle = {Proc. IEEE Conf. Control Technol. Appl.},
address = {Hong Kong, China},
year = {2019},
pages = {296--301},
month = August,
doi = {10.1109/CCTA.2019.8920458},
url = {https://ieeexplore.ieee.org/document/8920458},
}

G. Rotithor, R. Saltus, R. Kamalapurkar, and A. P. Dani, Observer design for structure from motion using concurrent learning, Proc. Am. Control Conf., pp. 2384-2389, 2019.
URLPreprint

@InProceedings{SCC.Rotithor.Saltus.ea2019,
author = {Rotithor, Ghananeel and Saltus, Ryan and Kamalapurkar, Rushikesh and Dani, Ashwin P.},
title = {Observer design for structure from motion using concurrent learning},
booktitle = {Proc. Am. Control Conf.},
address = {Philadelphia, PA, USA},
year = {2019},
pages = {2384--2389},
month = July,
doi = {10.23919/ACC.2019.8814784},
url = {https://ieeexplore.ieee.org/document/8814784},
}

R. V. Self, M. Harlan, and R. Kamalapurkar, Model-based reinforcement learning for output-feedback optimal control of a class of nonlinear systems, Proc. Am. Control Conf., pp. 2378-2383, 2019.
URLPreprint

@InProceedings{SCC.Self.Harlan.ea2019,
author = {Self, Ryan V. and Harlan, Michael and Kamalapurkar, Rushikesh},
title = {Model-based reinforcement learning for output-feedback optimal control of a class of nonlinear systems},
booktitle = {Proc. Am. Control Conf.},
address = {Philadelphia, PA, USA},
year = {2019},
pages = {2378--2383},
month = July,
doi = {10.23919/ACC.2019.8814910},
url = {https://ieeexplore.ieee.org/document/8814910},
}

J. A. Rosenfeld, R. Kamalapurkar, and W. E. Dixon, The state following approximation method, IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 6, pp. 1716-1730, 2019.
URLPreprint

@Article{SCC.Rosenfeld.Kamalapurkar.ea2019,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {The state following approximation method},
journal = {IEEE Trans. Neural Netw. Learn. Syst.},
year = {2019},
volume = {30},
number = {6},
pages = {1716--1730},
month = June,
doi = {10.1109/TNNLS.2018.2870040},
url = {https://ieeexplore.ieee.org/document/8509137},
}

R. Kamalapurkar, J. A. Rosenfeld, A. Parikh, A. R. Teel, and W. E. Dixon, Invariance-like results for switched nonautonomous nonsmooth systems, IEEE Trans. Autom. Control, vol. 64, no. 2, pp. 614-627, 2019.
URLPreprint

@Article{SCC.Kamalapurkar.Rosenfeld.ea2019,
author = {Kamalapurkar, Rushikesh and Rosenfeld, Joel A. and Parikh, Anup and Teel, Andrew R. and Dixon, Warren E.},
title = {Invariance-like results for switched nonautonomous nonsmooth systems},
journal = {IEEE Trans. Autom. Control},
year = {2019},
volume = {64},
number = {2},
pages = {614--627},
month = February,
doi = {10.1109/TAC.2018.2838055},
url = {https://ieeexplore.ieee.org/document/8360473},
}

M. Harlan, A method for solving switched optimal control problems with dwell time constraints, Oklahoma State University, 2019.
URLPreprint

@MastersThesis{SCC.Harlan2019,
author = {Michael Harlan},
title = {A method for solving switched optimal control problems with dwell time constraints},
institution = {Oklahoma State University},
year = {2019},
url = {https://www.proquest.com/docview/2409197601},
}

R. Kamalapurkar, Linear inverse reinforcement learning in continuous time and space, Proc. Am. Control Conf., pp. 1683-1688, 2018.
URLPreprint

@InProceedings{SCC.Kamalapurkar2018,
author = {Kamalapurkar, Rushikesh},
title = {Linear inverse reinforcement learning in continuous time and space},
booktitle = {Proc. Am. Control Conf.},
address = {Milwaukee, WI, USA},
year = {2018},
pages = {1683--1688},
month = June,
doi = {10.23919/ACC.2018.8431430},
url = {https://ieeexplore.ieee.org/document/8431430/},
}

A. Parikh, R. Kamalapurkar, and W. E. Dixon, Target tracking in the presence of intermittent measurements via motion model learning, IEEE Trans. Robot., vol. 34, no. 3, pp. 805-819, 2018.
URLPreprint

@Article{SCC.Parikh.Kamalapurkar.ea2018,
author = {Parikh, Anup and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Target tracking in the presence of intermittent measurements via motion model learning},
journal = {IEEE Trans. Robot.},
year = {2018},
volume = {34},
number = {3},
pages = {805--819},
month = May,
doi = {10.1109/TRO.2018.2821169},
url = {https://ieeexplore.ieee.org/document/8362797/},
}

P. Deptula, J. A. Rosenfeld, R. Kamalapurkar, and W. E. Dixon, Approximate dynamic programming: combining regional and local state following approximations, IEEE Trans. Neural Netw. Learn. Syst., vol. 29, no. 6, pp. 2154-2166, 2018.
URLPreprint

@Article{SCC.Deptula.Rosenfeld.ea2018,
author = {Deptula, Patryk and Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Approximate dynamic programming: combining regional and local state following approximations},
journal = {IEEE Trans. Neural Netw. Learn. Syst.},
year = {2018},
volume = {29},
number = {6},
pages = {2154--2166},
month = March,
doi = {10.1109/tnnls.2018.2808102},
url = {https://ieeexplore.ieee.org/document/8318392/},
}

R. Kamalapurkar, J. R. Klotz, P. Walters, and W. E. Dixon, Model-based reinforcement learning in differential graphical games, IEEE Trans. Control Netw. Syst., vol. 5, no. 1, pp. 423-433, 2018.
URLPreprintCode

@Article{SCC.Kamalapurkar.Klotz.ea2018,
author = {Kamalapurkar, Rushikesh and Klotz, Justin R. and Walters, Patrick and Dixon, Warren E.},
title = {Model-based reinforcement learning in differential graphical games},
journal = {IEEE Trans. Control Netw. Syst.},
year = {2018},
volume = {5},
number = {1},
pages = {423--433},
month = March,
doi = {10.1109/TCNS.2016.2617622},
url = {http://ieeexplore.ieee.org/document/7590053/},
}

P. Walters, R. Kamalapurkar, F. Voight, E. Schwartz, and W. E. Dixon, Online approximate optimal station keeping of a marine craft in the presence of an irrotational current, IEEE Trans. Robot., vol. 34, no. 2, pp. 486-496, 2018.
URLPreprint

@Article{SCC.Walters.Kamalapurkar.ea2018,
author = {Walters, Patrick and Kamalapurkar, Rushikesh and Voight, Forest and Schwartz, Eric and Dixon, Warren E.},
title = {Online approximate optimal station keeping of a marine craft in the presence of an irrotational current},
journal = {IEEE Trans. Robot.},
year = {2018},
volume = {34},
number = {2},
pages = {486--496},
month = March,
doi = {10.1109/TRO.2018.2791600},
url = {http://ieeexplore.ieee.org/document/8327868/},
}

R. Kamalapurkar, P. Walters, J. A. Rosenfeld, and W. E. Dixon, Reinforcement learning for optimal feedback control: A Lyapunov-based approach, ser. Communications and Control Engineering, Springer International Publishing, 2018.
URLCorrigendum

@Book{SCC.Kamalapurkar.Walters.ea2018,
author = {Kamalapurkar, Rushikesh and Walters, Patrick and Rosenfeld, Joel A. and Dixon, Warren E.},
title = {Reinforcement learning for optimal feedback control: {A} {L}yapunov-based approach},
publisher = {Springer International Publishing},
series = {Communications and Control Engineering},
year = {2018},
doi = {10.1007/978-3-319-78384-0},
url = {https://www.springer.com/us/book/9783319783833},
}

R. Kamalapurkar, W. E. Dixon, and A. R. Teel, On reduction of differential inclusions and Lyapunov stability, Proc. IEEE Conf. Decis. Control, pp. 5499-5504, 2017.
URLPreprint

@InProceedings{SCC.Kamalapurkar.Dixon.ea2017,
author = {Kamalapurkar, Rushikesh and Dixon, Warren E. and Teel, Andrew R.},
title = {On reduction of differential inclusions and {L}yapunov stability},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Melbourne, VIC, Australia},
year = {2017},
pages = {5499--5504},
month = December,
doi = {10.1109/CDC.2017.8264474},
url = {http://ieeexplore.ieee.org/document/8264474/},
}

R. Kamalapurkar, Simultaneous state and parameter estimation for second-order nonlinear systems, Proc. IEEE Conf. Decis. Control, pp. 2164-2169, 2017.
URLPreprint

@InProceedings{SCC.Kamalapurkar2017a,
author = {Kamalapurkar, Rushikesh},
title = {Simultaneous state and parameter estimation for second-order nonlinear systems},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Melbourne, VIC, Australia},
year = {2017},
pages = {2164--2169},
month = December,
doi = {10.1109/CDC.2017.8263965},
url = {http://ieeexplore.ieee.org/document/8263965/},
}

E. Ekanayake, R. Kamalapurkar, and J. Hausselle, Towards the development of a wearable skin to limit high joint contact forces: analysis of muscle co-contraction in lower extremities, Int. Symp. Wearable Robot. Rehabil., 2017, (abstract-reviewed poster).
URLPreprint

@Conference{SCC.Ekanayake.Kamalapurkar.ea2017,
author = {Ekanayake, Eranda and Kamalapurkar, Rushikesh and Hausselle, Jerome},
title = {Towards the development of a wearable skin to limit high joint contact forces: analysis of muscle co-contraction in lower extremities},
booktitle = {Int. Symp. Wearable Robot. Rehabil.},
address = {Houston, TX, USA},
year = {2017},
month = November,
doi = {10.1109/WEROB.2017.8383838},
note = {(abstract-reviewed poster)},
url = {https://ieeexplore.ieee.org/document/8383838},
}

R. Kamalapurkar, B. Reish, G. Chowdhary, and W. E. Dixon, Concurrent learning for parameter estimation using dynamic state-derivative estimators, IEEE Trans. Autom. Control, vol. 62, no. 7, pp. 3594-3601, 2017.
URLPreprint

@Article{SCC.Kamalapurkar.Reish.ea2017,
author = {Kamalapurkar, Rushikesh and Reish, Ben and Chowdhary, Girish and Dixon, Warren E.},
title = {Concurrent learning for parameter estimation using dynamic state-derivative estimators},
journal = {IEEE Trans. Autom. Control},
year = {2017},
volume = {62},
number = {7},
pages = {3594--3601},
month = July,
doi = {10.1109/TAC.2017.2671343},
url = {http://ieeexplore.ieee.org/document/7858671/},
}

H. T. Dinh, S. Bhasin, R. Kamalapurkar, and W. E. Dixon, Dynamic neural network-based output feedback tracking control for uncertain nonlinear systems, J. Dyn. Syst. Meas. Control, vol. 139, no. 7, 2017.
URLPreprint

@Article{SCC.Dinh.Bhasin.ea2017,
author = {Dinh, Huyen T. and Bhasin, Shubhendu and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Dynamic neural network-based output feedback tracking control for uncertain nonlinear systems},
journal = {J. Dyn. Syst. Meas. Control},
year = {2017},
volume = {139},
number = {7},
month = May,
doi = {10.1115/1.4035871},
url = {http://dynamicsystems.asmedigitalcollection.asme.org/article.aspx?articleid=2601294},
}

R. Kamalapurkar, Online output-feedback parameter and state estimation for second order linear systems, Proc. Am. Control Conf., pp. 5672-5677, 2017.
URLPreprint

@InProceedings{SCC.Kamalapurkar2017,
author = {Kamalapurkar, Rushikesh},
title = {Online output-feedback parameter and state estimation for second order linear systems},
booktitle = {Proc. Am. Control Conf.},
address = {Seattle, WA, USA},
year = {2017},
pages = {5672--5677},
month = May,
doi = {10.23919/ACC.2017.7963838},
url = {http://ieeexplore.ieee.org/document/7963838/},
}

R. Kamalapurkar, L. Andrews, P. Walters, and W. E. Dixon, Model-based reinforcement learning for infinite-horizon approximate optimal tracking, IEEE Trans. Neural Netw. Learn. Syst., vol. 28, no. 3, pp. 753-758, 2017.
URLPreprintCode

@Article{SCC.Kamalapurkar.Andrews.ea2017,
author = {Kamalapurkar, Rushikesh and Andrews, Lindsey and Walters, Patrick and Dixon, Warren E.},
title = {Model-based reinforcement learning for infinite-horizon approximate optimal tracking},
journal = {IEEE Trans. Neural Netw. Learn. Syst.},
year = {2017},
volume = {28},
number = {3},
pages = {753--758},
month = March,
doi = {10.1109/TNNLS.2015.2511658},
url = {http://ieeexplore.ieee.org/document/7398079/},
}

S. Obuz, J. R. Klotz, R. Kamalapurkar, and W. E. Dixon, Unknown time-varying input delay compensation for uncertain nonlinear systems, Automatica, vol. 76, pp. 222-229, 2017.
URLPreprint

@Article{SCC.Obuz.Klotz.ea2017,
author = {Obuz, Serhat and Klotz, Justin R. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Unknown time-varying input delay compensation for uncertain nonlinear systems},
journal = {Automatica},
year = {2017},
volume = {76},
pages = {222--229},
month = February,
doi = {10.1016/j.automatica.2016.09.030},
url = {http://www.sciencedirect.com/science/article/pii/S0005109816303752},
}

R. Kamalapurkar, J. A. Rosenfeld, and W. E. Dixon, Efficient model-based reinforcement learning for approximate online optimal control, Automatica, vol. 74, pp. 247-258, 2016.
URLPreprintCorrigendumCode

@Article{SCC.Kamalapurkar.Rosenfeld.ea2016,
author = {Kamalapurkar, Rushikesh and Rosenfeld, Joel A. and Dixon, Warren E.},
title = {Efficient model-based reinforcement learning for approximate online optimal control},
journal = {Automatica},
year = {2016},
volume = {74},
pages = {247--258},
month = December,
doi = {10.1016/j.automatica.2016.08.004},
url = {http://www.sciencedirect.com/science/article/pii/S0005109816303272},
}

R. Kamalapurkar, P. Walters, and W. E. Dixon, Model-based reinforcement learning for approximate optimal regulation, Control of Complex Systems: Theory and Applications, Kyriakos Vamvoudakis, and Sarangapani Jagannathan (Eds.), Butterworth-Heinemann, pp. 247-273, 2016.
URLPreprint

@InCollection{SCC.Kamalapurkar.Walters.ea2016a,
author = {Kamalapurkar, Rushikesh and Walters, Patrick and Dixon, Warren E.},
editor = {Kyriakos Vamvoudakis and Sarangapani Jagannathan},
title = {Model-based reinforcement learning for approximate optimal regulation},
booktitle = {Control of Complex Systems: Theory and Applications},
publisher = {Butterworth-Heinemann},
year = {2016},
pages = {247--273},
month = August,
doi = {10.1016/B978-0-12-805246-4.00008-2},
url = {http://www.sciencedirect.com/science/article/pii/B9780128052464000082},
}

T.-H. Cheng, Q. Wang, R. Kamalapurkar, H. T. Dinh, M. J. Bellman, and W. E. Dixon, Identification-based closed-loop NMES limb tracking with amplitude-modulated control input, IEEE Trans. Cybern., vol. 46, no. 7, pp. 1679-1690, 2016.
URLPreprint

@Article{SCC.Cheng.Wang.ea2016,
author = {Cheng, Teng-Hu and Wang, Quiang and Kamalapurkar, Rushikesh and Dinh, Huyen T. and Bellman, Michael J. and Dixon, Warren E.},
title = {Identification-based closed-loop {NMES} limb tracking with amplitude-modulated control input},
journal = {IEEE Trans. Cybern.},
year = {2016},
volume = {46},
number = {7},
pages = {1679--1690},
month = July,
doi = {10.1109/tcyb.2015.2453402},
url = {http://ieeexplore.ieee.org/document/7169519/},
}

R. J. Downey, R. Kamalapurkar, N. Fischer, and W. E. Dixon, Compensating for fatigue-induced time-varying delayed muscle response in neuromuscular electrical stimulation control, Recent Results on Nonlinear Delay Control Systems: In honor of Miroslav Krstic, ser. Advances in Delays and Dynamics, vol. 4, I. Karafyllis, M. Malisoff, F. Mazenc, and P. Pepe (Eds.), Springer International Publishing, pp. 143-161, 2016.
URLPreprint

@InCollection{SCC.Downey.Kamalapurkar.ea2016,
author = {Downey, Ryan J. and Kamalapurkar, Rushikesh and Fischer, Nicholas and Dixon, Warren E.},
editor = {I. Karafyllis and M. Malisoff and F. Mazenc and P. Pepe},
title = {Compensating for fatigue-induced time-varying delayed muscle response in neuromuscular electrical stimulation control},
booktitle = {Recent Results on Nonlinear Delay Control Systems: {I}n honor of {M}iroslav {K}rstic},
publisher = {Springer International Publishing},
series = {Advances in Delays and Dynamics},
year = {2016},
volume = {4},
pages = {143--161},
month = July,
doi = {10.1007/978-3-319-18072-4_7},
url = {http://link.springer.com/chapter/10.1007%2F978-3-319-18072-4_7},
}

R. Kamalapurkar, N. Fischer, S. Obuz, and W. E. Dixon, Time-varying input and state delay compensation for uncertain nonlinear systems, IEEE Trans. Autom. Control, vol. 61, no. 3, pp. 834-839, 2016.
URLPreprintCode

@Article{SCC.Kamalapurkar.Fischer.ea2016,
author = {Kamalapurkar, Rushikesh and Fischer, Nicholas and Obuz, Serhat and Dixon, Warren E.},
title = {Time-varying input and state delay compensation for uncertain nonlinear systems},
journal = {IEEE Trans. Autom. Control},
year = {2016},
volume = {61},
number = {3},
pages = {834--839},
month = March,
doi = {10.1109/tac.2015.2451472},
url = {http://ieeexplore.ieee.org/document/7140771/},
}

R. Kamalapurkar, P. Walters, and W. E. Dixon, Model-based reinforcement learning for approximate optimal regulation, Automatica, vol. 64, pp. 94-104, 2016.
URLPreprintCode

@Article{SCC.Kamalapurkar.Walters.ea2016,
author = {Kamalapurkar, Rushikesh and Walters, Patrick and Dixon, Warren E.},
title = {Model-based reinforcement learning for approximate optimal regulation},
journal = {Automatica},
year = {2016},
volume = {64},
pages = {94--104},
month = February,
doi = {10.1016/j.automatica.2015.10.039},
url = {http://www.sciencedirect.com/science/article/pii/S0005109815004392},
}

A. Parikh, R. Kamalapurkar, and W. E. Dixon, Data-based learning for uncertain robotic systems, Adaptive Control for Robotic Manipulators, Dan Zhang, and Bin Wei (Eds.), CRC Press, pp. 40-48, 2016.
URLPreprint

@InCollection{SCC.Parikh.Kamalapurkar.ea2016,
author = {Parikh, Anup and Kamalapurkar, Rushikesh and Dixon, Warren E.},
editor = {Dan Zhang and Bin Wei},
title = {Data-based learning for uncertain robotic systems},
booktitle = {Adaptive Control for Robotic Manipulators},
publisher = {CRC Press},
year = {2016},
pages = {40--48},
doi = {10.1201/9781315166056},
url = {https://www.taylorfrancis.com/books/9781315166056},
}

A. Parikh, R. Kamalapurkar, H.-Y. Chen, and W. E. Dixon, Homography based visual servo control with scene reconstruction, Proc. IEEE Conf. Decis. Control, pp. 6972-6977, 2015.
URLPreprint

@InProceedings{SCC.Parikh.Kamalapurkar.ea2015,
author = {Parikh, Anup and Kamalapurkar, Rushikesh and Chen, Hsi-Yuan and Dixon, Warren E.},
title = {Homography based visual servo control with scene reconstruction},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Osaka, Japan},
year = {2015},
pages = {6972--6977},
month = December,
doi = {10.1109/cdc.2015.7403318},
url = {https://ieeexplore.ieee.org/document/7403318},
}

P. Walters, R. Kamalapurkar, and W. E. Dixon, Approximate optimal online continuous-time path-planner with static obstacle avoidance, Proc. IEEE Conf. Decis. Control, pp. 650-655, 2015.
URLPreprint

@InProceedings{SCC.Walters.Kamalapurkar.ea2015,
author = {Walters, Patrick and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Approximate optimal online continuous-time path-planner with static obstacle avoidance},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Osaka, Japan},
year = {2015},
pages = {650--655},
month = December,
doi = {10.1109/cdc.2015.7402303},
url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7402303},
}

M. Johnson, R. Kamalapurkar, S. Bhasin, and W. E. Dixon, Approximate N-player nonzero-sum game solution for an uncertain continuous nonlinear system, IEEE Trans. Neural Netw. Learn. Syst., vol. 26, no. 8, pp. 1645-1658, 2015.
URLPreprint

@Article{SCC.Johnson.Kamalapurkar.ea2015,
author = {Johnson, Marcus and Kamalapurkar, Rushikesh and Bhasin, Shubhendu and Dixon, Warren E.},
title = {Approximate {$N$}-player nonzero-sum game solution for an uncertain continuous nonlinear system},
journal = {IEEE Trans. Neural Netw. Learn. Syst.},
year = {2015},
volume = {26},
number = {8},
pages = {1645--1658},
month = August,
doi = {10.1109/tnnls.2014.2350835},
url = {http://ieeexplore.ieee.org/document/6918499/},
}

R. Kamalapurkar, J. A. Rosenfeld, and W. E. Dixon, State following (StaF) kernel functions for function approximation Part II: Adaptive dynamic programming, Proc. Am. Control Conf., pp. 521-526, 2015.
URLPreprint

@InProceedings{SCC.Kamalapurkar.Rosenfeld.ea2015,
author = {Kamalapurkar, Rushikesh and Rosenfeld, Joel A. and Dixon, Warren E.},
title = {State following ({S}ta{F}) kernel functions for function approximation {P}art {II}: {A}daptive dynamic programming},
booktitle = {Proc. Am. Control Conf.},
address = {Chicago, IL, USA},
year = {2015},
pages = {521--526},
month = July,
doi = {10.1109/acc.2015.7170788},
url = {https://ieeexplore.ieee.org/document/7170788},
}

J. R. Klotz, L. Andrews, R. Kamalapurkar, and W. E. Dixon, Decentralized monitoring of leader-follower networks of uncertain nonlinear systems, Proc. Am. Control Conf., pp. 1393-1398, 2015.
URLPreprint

@InProceedings{SCC.Klotz.Andrews.ea2015,
author = {Klotz, Justin R. and Andrews, Lindsey and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Decentralized monitoring of leader-follower networks of uncertain nonlinear systems},
booktitle = {Proc. Am. Control Conf.},
address = {Chicago, IL, USA},
year = {2015},
pages = {1393--1398},
month = July,
doi = {10.1109/acc.2015.7170928},
url = {https://ieeexplore.ieee.org/document/7170928},
}

J. A. Rosenfeld, R. Kamalapurkar, and W. E. Dixon, State following (StaF) kernel functions for function approximation Part I: Theory and motivation, Proc. Am. Control Conf., pp. 1217-1222, 2015.
URLPreprint

@InProceedings{SCC.Rosenfeld.Kamalapurkar.ea2015,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {State following ({S}ta{F}) kernel functions for function approximation {P}art {I}: {T}heory and motivation},
booktitle = {Proc. Am. Control Conf.},
address = {Chicago, IL, USA},
year = {2015},
pages = {1217--1222},
month = July,
doi = {10.1109/acc.2015.7170899},
url = {https://ieeexplore.ieee.org/document/7170899},
}

R. Kamalapurkar, H. T. Dinh, S. Bhasin, and W. E. Dixon, Approximate optimal trajectory tracking for continuous-time nonlinear systems, Automatica, vol. 51, pp. 40-48, 2015.
URLPreprintCorrigendumCode

@Article{SCC.Kamalapurkar.Dinh.ea2015,
author = {Kamalapurkar, Rushikesh and Dinh, Huyen T. and Bhasin, Shubhendu and Dixon, Warren E.},
title = {Approximate optimal trajectory tracking for continuous-time nonlinear systems},
journal = {Automatica},
year = {2015},
volume = {51},
pages = {40--48},
month = January,
doi = {10.1016/j.automatica.2014.10.103},
url = {http://www.sciencedirect.com/science/article/pii/S0005109814004841},
}

L. Andrews, J. R. Klotz, R. Kamalapurkar, and W. E. Dixon, Adaptive dynamic programming for terminally constrained finite-horizon optimal control problems, Proc. IEEE Conf. Decis. Control, pp. 5095-5100, 2014.
URLPreprint

@InProceedings{SCC.Andrews.Klotz.ea2014,
author = {Andrews, Lindsey and Klotz, Justin R. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Adaptive dynamic programming for terminally constrained finite-horizon optimal control problems},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Los Angeles, CA, USA},
year = {2014},
pages = {5095--5100},
month = December,
doi = {10.1109/cdc.2014.7040185},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7040185&isnumber=7039338},
}

H. T. Dinh, R. Kamalapurkar, S. Bhasin, and W. E. Dixon, Dynamic neural network-based robust observers for uncertain nonlinear systems, Neural Netw., vol. 60, pp. 44-52, 2014.
URLPreprint

@Article{SCC.Dinh.Kamalapurkar.ea2014,
author = {Dinh, Huyen T. and Kamalapurkar, Rushikesh and Bhasin, Shubhendu and Dixon, Warren E.},
title = {Dynamic neural network-based robust observers for uncertain nonlinear systems},
journal = {Neural Netw.},
year = {2014},
volume = {60},
pages = {44--52},
month = December,
doi = {10.1016/j.neunet.2014.07.009},
url = {http://www.sciencedirect.com/science/article/pii/S089360801400166X},
}

R. Kamalapurkar, L. Andrews, P. Walters, and W. E. Dixon, Model-based reinforcement learning for infinite-horizon approximate optimal tracking, Proc. IEEE Conf. Decis. Control, pp. 5083-5088, 2014.
URLPreprint

@InProceedings{SCC.Kamalapurkar.Andrews.ea2014,
author = {Kamalapurkar, Rushikesh and Andrews, Lindsey and Walters, Patrick and Dixon, Warren E.},
title = {Model-based reinforcement learning for infinite-horizon approximate optimal tracking},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Los Angeles, CA, USA},
year = {2014},
pages = {5083--5088},
month = December,
doi = {10.1109/cdc.2014.7040183},
url = {https://ieeexplore.ieee.org/document/7040183},
}

P. Walters, R. Kamalapurkar, L. Andrews, and W. E. Dixon, Online approximate optimal path-following for a mobile robot, Proc. IEEE Conf. Decis. Control, pp. 4536-4541, 2014.
URLPreprint

@InProceedings{SCC.Walters.Kamalapurkar.ea2014,
author = {Walters, Patrick and Kamalapurkar, Rushikesh and Andrews, Lindsey and Dixon, Warren E.},
title = {Online approximate optimal path-following for a mobile robot},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Los Angeles, CA, USA},
year = {2014},
pages = {4536--4541},
month = December,
doi = {10.1109/cdc.2014.7040097},
url = {https://ieeexplore.ieee.org/document/7040097},
}

R. Kamalapurkar, J. R. Klotz, and W. E. Dixon, Concurrent learning-based online approximate feedback Nash equilibrium solution of N-player nonzero-sum differential games, IEEE/CAA J. Autom. Sin., vol. 1, no. 3, pp. 239-247, 2014, Special Issue on Extensions of Reinforcement Learning and Adaptive Control.
URLPreprintCode

@Article{SCC.Kamalapurkar.Klotz.ea2014a,
author = {Kamalapurkar, Rushikesh and Klotz, Justin R. and Dixon, Warren E.},
title = {Concurrent learning-based online approximate feedback {N}ash equilibrium solution of {$N$}-player nonzero-sum differential games},
journal = {IEEE/CAA J. Autom. Sin.},
year = {2014},
volume = {1},
number = {3},
pages = {239--247},
month = July,
doi = {10.1109/JAS.2014.7004681},
note = {{S}pecial Issue on Extensions of Reinforcement Learning and Adaptive Control},
url = {http://ieeexplore.ieee.org/document/7004681},
}

R. Kamalapurkar, J. R. Klotz, and W. E. Dixon, Model-based reinforcement learning for on-line feedback-Nash equilibrium solution of N-player nonzero-sum differential games, Proc. Am. Control Conf., pp. 3000-3005, 2014.
URLPreprint

@InProceedings{SCC.Kamalapurkar.Klotz.ea2014,
author = {Kamalapurkar, Rushikesh and Klotz, Justin R. and Dixon, Warren E.},
title = {Model-based reinforcement learning for on-line feedback-{N}ash equilibrium solution of {$N$}-player nonzero-sum differential games},
booktitle = {Proc. Am. Control Conf.},
address = {Portland, OR, USA},
year = {2014},
pages = {3000--3005},
month = June,
doi = {10.1109/acc.2014.6859092},
url = {https://ieeexplore.ieee.org/document/6859092},
}

J. R. Klotz, R. Kamalapurkar, and W. E. Dixon, Concurrent learning-based network synchronization, Proc. Am. Control Conf., pp. 796-801, 2014.
URLPreprint

@InProceedings{SCC.Klotz.Kamalapurkar.ea2014,
author = {Klotz, Justin R. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Concurrent learning-based network synchronization},
booktitle = {Proc. Am. Control Conf.},
address = {Portland, OR, USA},
year = {2014},
pages = {796--801},
month = June,
doi = {10.1109/acc.2014.6859099},
url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6859099&isnumber=6858556},
}

N. Fischer, Z. Kan, R. Kamalapurkar, and W. E. Dixon, Saturated RISE feedback control for a class of second-order nonlinear systems, IEEE Trans. Autom. Control, vol. 59, no. 4, pp. 1094-1099, 2014.
URLPreprintCode

@Article{SCC.Fischer.Kan.ea2014,
author = {Fischer, Nicholas and Kan, Zhen and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Saturated {RISE} feedback control for a class of second-order nonlinear systems},
journal = {IEEE Trans. Autom. Control},
year = {2014},
volume = {59},
number = {4},
pages = {1094--1099},
month = April,
doi = {10.1109/tac.2013.2286913},
url = {http://ieeexplore.ieee.org/document/6645414/},
}

R. Kamalapurkar, Model-based reinforcement learning for online approximate optimal control, University of Florida, 2014.
URLPreprint

@PhdThesis{SCC.Kamalapurkar2014,
author = {Kamalapurkar, Rushikesh},
title = {Model-based reinforcement learning for online approximate optimal control},
institution = {University of Florida},
year = {2014},
url = {https://uf.catalog.fcla.edu/permalink.jsp?20UF033651110},
}

R. Kamalapurkar, P. Walters, and W. E. Dixon, Concurrent learning-based approximate optimal regulation, Proc. IEEE Conf. Decis. Control, pp. 6256-6261, 2013.
URLPreprint

@InProceedings{SCC.Kamalapurkar.Walters.ea2013,
author = {Kamalapurkar, Rushikesh and Walters, Patrick and Dixon, Warren E.},
title = {Concurrent learning-based approximate optimal regulation},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Florence, Italy},
year = {2013},
pages = {6256--6261},
month = December,
doi = {10.1109/cdc.2013.6760878},
url = {https://ieeexplore.ieee.org/document/6760878},
}

N. Fischer, R. Kamalapurkar, and W. E. Dixon, LaSalle-Yoshizawa corollaries for nonsmooth systems, IEEE Trans. Autom. Control, vol. 58, no. 9, pp. 2333-2338, 2013.
URLPreprint

@Article{SCC.Fischer.Kamalapurkar.ea2013,
author = {Fischer, Nicholas and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {La{S}alle-{Y}oshizawa corollaries for nonsmooth systems},
journal = {IEEE Trans. Autom. Control},
year = {2013},
volume = {58},
number = {9},
pages = {2333--2338},
month = September,
doi = {10.1109/tac.2013.2246900},
url = {http://ieeexplore.ieee.org/document/6508855/},
}

R. Kamalapurkar, B. Bialy, L. Andrews, and W. E. Dixon, Adaptive rise feedback control strategies for systems with structured and unstructured uncertainties, Proc. AIAA Guid. Navig. Control Conf., 2013.
URLPreprint

@InProceedings{SCC.Kamalapurkar.Bialy.ea2013,
author = {Kamalapurkar, Rushikesh and Bialy, Brendan and Andrews, Lindsey and Dixon, Warren E.},
title = {Adaptive rise feedback control strategies for systems with structured and unstructured uncertainties},
booktitle = {Proc. AIAA Guid. Navig. Control Conf.},
address = {Boston, MA, USA},
year = {2013},
month = August,
doi = {10.2514/6.2013-4852},
url = {http://arc.aiaa.org/doi/abs/10.2514/6.2013-4852},
}

H. T. Dinh, N. Fischer, R. Kamalapurkar, and W. E. Dixon, Output feedback control for uncertain nonlinear systems with slowly varying input delay, Proc. Am. Control Conf., pp. 1748-1753, 2013.
URLPreprint

@InProceedings{SCC.Dinh.Fischer.ea2013,
author = {Dinh, Huyen T. and Fischer, Nicholas and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Output feedback control for uncertain nonlinear systems with slowly varying input delay},
booktitle = {Proc. Am. Control Conf.},
address = {Washington, DC, USA},
year = {2013},
pages = {1748--1753},
month = June,
doi = {10.1109/acc.2013.6580088},
url = {https://ieeexplore.ieee.org/document/6580088},
}

R. Kamalapurkar, H. T. Dinh, P. Walters, and W. E. Dixon, Approximate optimal cooperative decentralized control for consensus in a topological network of agents with uncertain nonlinear dynamics, Proc. Am. Control Conf., pp. 1322-1327, 2013.
URLPreprintCorrigendum

@InProceedings{SCC.Kamalapurkar.Dinh.ea2013,
author = {Kamalapurkar, Rushikesh and Dinh, Huyen T. and Walters, Patrick and Dixon, Warren E.},
title = {Approximate optimal cooperative decentralized control for consensus in a topological network of agents with uncertain nonlinear dynamics},
booktitle = {Proc. Am. Control Conf.},
address = {Washington, DC, USA},
year = {2013},
pages = {1322--1327},
month = June,
doi = {10.1109/acc.2013.6580019},
url = {https://ieeexplore.ieee.org/document/6580019},
}

S. Bhasin, R. Kamalapurkar, H. T. Dinh, and W. E. Dixon, Robust identification-based state derivative estimation for nonlinear systems, IEEE Trans. Autom. Control, vol. 58, no. 1, pp. 187-192, 2013.
URLPreprint

@Article{SCC.Bhasin.Kamalapurkar.ea2013,
author = {Bhasin, Shubhendu and Kamalapurkar, Rushikesh and Dinh, Huyen T. and Dixon, Warren E.},
title = {Robust identification-based state derivative estimation for nonlinear systems},
journal = {IEEE Trans. Autom. Control},
year = {2013},
volume = {58},
number = {1},
pages = {187--192},
month = January,
doi = {10.1109/tac.2012.2203452},
url = {http://ieeexplore.ieee.org/document/6212314/},
}

S. Bhasin, R. Kamalapurkar, M. Johnson, K. G. Vamvoudakis, F. L. Lewis, and W. E. Dixon, A novel actor-critic-identifier architecture for approximate optimal control of uncertain nonlinear systems, Automatica, vol. 49, no. 1, pp. 89-92, 2013.
URLPreprint

@Article{SCC.Bhasin.Kamalapurkar.ea2013a,
author = {Bhasin, Shubhendu and Kamalapurkar, Rushikesh and Johnson, Marcus and Vamvoudakis, Kyriakos G. and Lewis, Frank L. and Dixon, Warren E.},
title = {A novel actor-critic-identifier architecture for approximate optimal control of uncertain nonlinear systems},
journal = {Automatica},
year = {2013},
volume = {49},
number = {1},
pages = {89--92},
month = January,
doi = {10.1016/j.automatica.2012.09.019},
url = {http://www.sciencedirect.com/science/article/pii/S0005109812004827},
}

N. Fischer, R. Kamalapurkar, N. Sharma, and W. E. Dixon, RISE-based control of an uncertain nonlinear system with time-varying state delays, Proc. IEEE Conf. Decis. Control, pp. 3502-3507, 2012.
URLPreprint

@InProceedings{SCC.Fischer.Kamalapurkar.ea2012a,
author = {Fischer, Nicholas and Kamalapurkar, Rushikesh and Sharma, Nitin and Dixon, Warren E.},
title = {{RISE}-based control of an uncertain nonlinear system with time-varying state delays},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Maui, HI, USA},
year = {2012},
pages = {3502--3507},
month = December,
doi = {10.1109/cdc.2012.6427002},
url = {https://ieeexplore.ieee.org/document/6427002},
}

Q. Wang, R. Kamalapurkar, R. J. Downey, and W. E. Dixon, Hybrid electrical stimulation tracking control of the ankle, Proc. ASME Dyn. Syst. Control Conf., 2012.
URLPreprint

@InProceedings{SCC.Wang.Kamalapurkar.ea2012,
author = {Wang, Quiang and Kamalapurkar, Rushikesh and Downey, Ryan J. and Dixon, Warren E.},
title = {Hybrid electrical stimulation tracking control of the ankle},
booktitle = {Proc. ASME Dyn. Syst. Control Conf.},
address = {Ft. Lauderdale, FL, USA},
year = {2012},
month = October,
doi = {10.1115/dscc2012-movic2012-8683},
url = {http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=1739261},
}

N. Fischer, R. Kamalapurkar, N. Fitz-Coy, and W. E. Dixon, Lyapunov-based control of an uncertain Euler-Lagrange system with time-varying input delay, Proc. Am. Control Conf., pp. 3919-3924, 2012.
URLPreprint

@InProceedings{SCC.Fischer.Kamalapurkar.ea2012,
author = {Fischer, Nicholas and Kamalapurkar, Rushikesh and Fitz-Coy, Norman and Dixon, Warren E.},
title = {Lyapunov-based control of an uncertain {E}uler-{L}agrange system with time-varying input delay},
booktitle = {Proc. Am. Control Conf.},
address = {Montr\'{e}al, Canada},
year = {2012},
pages = {3919--3924},
month = June,
doi = {10.1109/acc.2012.6315102},
url = {https://ieeexplore.ieee.org/document/6315102},
}

S. Bhasin, R. Kamalapurkar, M. Johnson, K. G. Vamvoudakis, F. L. Lewis, and W. E. Dixon, An actor-critic-identifier architecture for adaptive approximate optimal control, Reinforcement Learning and Approximate Dynamic Programming for Feedback Control, ser. IEEE Press Series on Computational Intelligence, F. L. Lewis, and D. Liu (Eds.), Wiley and IEEE Press, pp. 258-278, 2012.
URLPreprint

@InCollection{SCC.Bhasin.Kamalapurkar.ea2012,
author = {Bhasin, Shubhendu and Kamalapurkar, Rushikesh and Johnson, Marcus and Vamvoudakis, Kyriakos G. and Lewis, Frank L. and Dixon, Warren E.},
editor = {F. L. Lewis and D. Liu},
title = {An actor-critic-identifier architecture for adaptive approximate optimal control},
booktitle = {Reinforcement Learning and Approximate Dynamic Programming for Feedback Control},
publisher = {Wiley and IEEE Press},
series = {IEEE Press Series on Computational Intelligence},
year = {2012},
pages = {258--278},
month = February,
doi = {10.1002/9781118453988.ch12},
url = {http://onlinelibrary.wiley.com/doi/10.1002/9781118453988.ch12/summary},
}

H. T. Dinh, R. Kamalapurkar, S. Bhasin, and W. E. Dixon, Dynamic neural network-based robust observers for second-order uncertain nonlinear systems, Proc. IEEE Conf. Decis. Control, pp. 7543-7548, 2011.
URLPreprint

@InProceedings{SCC.Dinh.Kamalapurkar.ea2011,
author = {Dinh, Huyen T. and Kamalapurkar, Rushikesh and Bhasin, Shubhendu and Dixon, Warren E.},
title = {Dynamic neural network-based robust observers for second-order uncertain nonlinear systems},
booktitle = {Proc. IEEE Conf. Decis. Control},
address = {Orlando, FL, USA},
year = {2011},
pages = {7543--7548},
month = December,
doi = {10.1109/cdc.2011.6160981},
url = {https://ieeexplore.ieee.org/document/6160981},
}

R. Kamalapurkar, and P. P. Date, Minimizing wastage of sheet metal for economical manufacturing, J. Mater. Process. Technol., vol. 177, no. 1, pp. 81-83, 2006.
URLPreprint

@Article{SCC.Kamalapurkar.Date2006,
author = {Kamalapurkar, Rushikesh and Date, Prashant P.},
title = {Minimizing wastage of sheet metal for economical manufacturing},
journal = {J. Mater. Process. Technol.},
year = {2006},
volume = {177},
number = {1},
pages = {81--83},
month = July,
doi = {10.1016/j.jmatprotec.2006.03.179},
url = {http://www.sciencedirect.com/science/article/pii/S0924013606003517},
}

E. H. Gonzalez, M. Abudia, M. Jury, R. Kamalapurkar, and J. A. Rosenfeld, The kernel perspective on dynamic mode decomposition, Trans. Mach. Learn. Res., to appear.
Preprint

@Article{SCC.Gonzalez.Abudia.eatoappear,
author = {Gonzalez, Efrain H. and Abudia, Moad and Jury, Michael and Kamalapurkar, Rushikesh and Rosenfeld, Joel A.},
title = {The kernel perspective on dynamic mode decomposition},
journal = {Trans. Mach. Learn. Res.},
year = {to appear},
}

M. L. Greene, M. S. Sakha, R. Kamalapurkar, and W. E. Dixon, Approximate dynamic programming for practical stabilization of switched systems, IEEE Trans. Autom. Control, to appear.
Preprint

@Article{SCC.Greene.Sakha.eatoappear,
author = {Greene, Max L. and Sakha, Masoud S. and Kamalapurkar, Rushikesh and Dixon, Warren E.},
title = {Approximate dynamic programming for practical stabilization of switched systems},
journal = {IEEE Trans. Autom. Control},
year = {to appear},
}

J. A. Rosenfeld, and R. Kamalapurkar, Dynamic mode decomposition with control Liouville operators, IEEE Trans. Autom. Control, to appear.
URLPreprint

@Article{SCC.Rosenfeld.Kamalapurkartoappear,
author = {Rosenfeld, Joel A. and Kamalapurkar, Rushikesh},
title = {Dynamic mode decomposition with control {L}iouville operators},
journal = {IEEE Trans. Autom. Control},
year = {to appear},
doi = {10.1109/TAC.2024.3419179},
url = {https://ieeexplore.ieee.org/document/10572269},
}

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