10 citations · 29 across the 13 of their papers we have counts for
11 papers · 1 filter
Koopman-based Policy Iteration for Robust Optimal Control
Alexander Krolicki, Sarang Sutavani, Umesh Vaidya
Classically, the optimal control problem in the presence of an adversary is formulated as a two-player zero-sum differential game or an control problem. The solution to…
Data-Driven Optimal Control via Linear Transfer Operators: A Convex Approach
Joseph Moyalan, Hyungjin Choi, Yongxin Chen +1
This paper is concerned with data-driven optimal control of nonlinear systems. We present a convex formulation to the optimal control problem (OCP) with a discounted cost function.…
Data-Driven Stochastic Optimal Control using Linear Transfer Operators
Umesh Vaidya, Duvan Tellez-Castro
We provide a data-driven framework for optimal control of a continuous-time stochastic dynamical system. The proposed framework relies on the linear operator theory involving linea…
A Convex Approach to Data-driven Optimal Control via Perron-Frobenius and Koopman Operators
Bowen Huang, Umesh Vaidya
The paper is about the data-driven computation of optimal control for a class of control affine deterministic nonlinear systems. We assume that the control dynamical system model i…
Data-Driven Nonlinear Stabilization Using Koopman Operator
Bowen Huang, Xu Ma, Umesh Vaidya
We propose the application of Koopman operator theory for the design of stabilizing feedback controller for a nonlinear control system. The proposed approach is data-driven and rel…
Sample Complexity for Nonlinear Dynamics
Yongxin Chen, Umesh Vaidya
We consider the identification problems for nonlinear dynamical systems. An explicit sample complexity bound in terms of the number of data points required to recover the models ac…