Neural critic learning toward robust dynamic stabilization

Abstract

Summary In this article, we focus on developing a neural‐network‐based critic learning strategy toward robust dynamic stabilization for a class of uncertain nonlinear systems. A type of general uncertainties involved both in the internal dynamics and in the input matrix is considered. An auxiliary system with actual action and auxiliary signal is constructed after dynamics decomposition and combination for the original plant. The reasonability of the control problem transformation from robust stabilization to optimal feedback design is also provided theoretically. After that, the adaptive critic learning method based on a neural network is established to derive the approximate optimal solution of the transformed control problem. The critic weight can be initialized to a zero vector, which apparently facilitates the learning process. Numerical simulation is finally presented to illustrate the effectiveness of the critic learning approach for neural robust stabilization.

Adaptive optimal tracking control with novel event‐triggered formulation for a type of nonlinear systems

“…In the optimal regulation process, it is difficult to employ other control methods. Over the past decades, ADP has been widely studied in References 5‐26. As stated in the survey, 5 ADP algorithms in terms of iteration can be divided into two categories: value iteration 6‐12 and policy iteration 13‐15 .…”

Multi‐event‐triggered adaptive critic control with guaranteed cost for discrete‐time nonlinear nonzero‐sum games

“…12,13 As stated in the survey, 14 ADP algorithms in terms of iteration can be divided into two categories: value iteration 15,16 and policy iteration. 17,18 So far, a large number of results based on ADP have been obtained to solve various control problems, such as optimal control with constrained control inputs, [19][20][21] optimal tracking control, [22][23][24] networked control, 25 robust control, 26,27 and event-triggered control, [28][29][30] which strongly show the applicability and great potential of ADP algorithms. In Reference 16, the convergence of the adaptive critic algorithm was proven and the algorithm procedure was given.…”

Intelligent optimal tracking with asymmetric constraints of a nonlinear wastewater treatment system

“…ADP mechanism mainly includes six structures, among which heuristic dynamic programming (HDP), dual HDP (DHP) are most widely used 15,16 . Nowadays, ADP mechanism has been extensively studied and applied to address optimal regulation, 17,18 tracking control, 19‐21 control constraints, 22,23 robust stabilization, 24,25 power system control, 26 and so on.…”