In this effort, we are developing novel operator theoretic techniques for data and model-driven synthesis of control policies through synthesis of control Lyapunov functions and solution of optimal control problems. The proposed technical tasks focus on the use of trajectories (i.e., time-series) as the fundamental unit of data for the resolution of control synthesis and certification problems in dynamical systems. Trajectory information in the dynamical systems is embedded in a reproducing kernel Hilbert space (RKHS) through what will be called occupation kernels. The occupation kernels are tied to the dynamics of the system through the densely defined Liouville operator. The pairing of Liouville operators and occupation kernels results in an operator theoretic framework that allows for nontrivial information concerning the dynamical systems to be extracted from the RKHS.


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