This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent …
M Ha, D Wang, D Liu - IEEE/CAA Journal of Automatica Sinica, 2022 - ieeexplore.ieee.org
The core task of tracking control is to make the controlled plant track a desired trajectory. The traditional performance index used in previous studies cannot eliminate completely the …
We consider the problem of optimal trajectory tracking for unknown systems. A novel data- enabled predictive control (DeePC) algorithm is presented that computes optimal and safe …
In this paper, we investigate the learning-based adaptive optimal output regulation problem with convergence rate requirement for disturbed linear continuous-time systems. An …
This paper deals with the design of an H∞ tracking controller for nonlinear continuous-time systems with completely unknown dynamics. A general bounded L 2-gain tracking problem …
M Zhao, D Wang, J Qiao, M Ha, J Ren - Artificial Intelligence Review, 2023 - Springer
Optimal control problems are ubiquitous in practical engineering applications and social life with the idea of cost or resource conservation. Based on the critic learning scheme, adaptive …
In this paper, a new formulation for the optimal tracking control problem (OTCP) of continuous-time nonlinear systems is presented. This formulation extends the integral …
C Li, J Ding, FL Lewis, T Chai - Automatica, 2021 - Elsevier
In this paper, to eliminate the tracking error by using adaptive dynamic programming (ADP) algorithms, a novel formulation of the value function is presented for the optimal tracking …
Model-free control is an important and promising topic in control fields, which has attracted extensive attention in the past few years. In this paper, we aim to solve the model-free …