10 citations · 29 across the 16 of their papers we have counts for
4 papers · 1 filter
Deep Learning of Koopman Representation for Control
Yiqiang Han, Wenjian Hao, Umesh Vaidya
We develop a data-driven, model-free approach for the optimal control of the dynamical system. The proposed approach relies on the Deep Neural Network (DNN) based learning of Koopm…
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…
A convex data-driven approach for nonlinear control synthesis
Hyungjin Choi, Umesh Vaidya, Yongxin Chen
We consider a class of nonlinear control synthesis problems where the underlying mathematical models are not explicitly known. We propose a data-driven approach to stabilize the sy…
Data-Driven Approach for Uncertainty Propagation and Reachability Analysis in Dynamical Systems
Amarsagar Reddy Ramapuram Matavalam, Umesh Vaidya, Venkataramana Ajjarapu
In this paper, we propose a data-driven approach for uncertainty propagation and reachability analysis in a dynamical system. The proposed approach relies on the linear lifting of…