Convergence and Robustness of Value and Policy Iteration for the Linear Quadratic Regulator

Autor:	Song, Bowen, Wu, Chenxuan, Iannelli, Andrea
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Systems and Control 49N10
Druh dokumentu:	Working Paper
Popis:	This paper revisits and extends the convergence and robustness properties of value and policy iteration algorithms for discrete-time linear quadratic regulator problems. In the model-based case, we extend current results concerning the region of exponential convergence of both algorithms. In the case where there is uncertainty on the value of the system matrices, we provide input-to-state stability results capturing the effect of model parameter uncertainties. Our findings offer new insights into these algorithms at the heart of several approximate dynamic programming schemes, highlighting their convergence and robustness behaviors. Numerical examples illustrate the significance of some of the theoretical results. Comment: This work has been submitted to the European Control Conference 2025
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2411.04548 Zobrazit plný text záznamu View this record from Arxiv