Adaptive Dynamic Programming for Networked Control Systems Under Communication Constraints: A Survey of Trends and Techniques

Abstract

Survey/review study Adaptive Dynamic Programming for Networked Control Systems under Communication Constraints: A Survey of Trends and Techniques Xueli Wang 1, Ying Sun 1,*, and Derui Ding 2 1 Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China 2 School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne 3122, Australia * Correspondence: yingsun1991@163.com     Received: 22 September 2022 Accepted: 28 November 2022 Published: 22 December 2022   Abstract: The adaptive dynamic programming (ADP) technology has been widely used benefiting from its recursive structure in forward and the prospective conception of reinforcement learning. Furthermore, ADP-based control issues with communication constraints arouse ever-increasing research consideration in theoretical analysis and engineering applications due mainly to the wide participation of digital communications in industrial systems. The latest development of ADP-based optimal control with communication constraints is systematically surveyed in this paper. To this end, the development of ADP-based dominant methods is first investigated from their structures and implementation. Then, technical challenges and corresponding approaches are comprehensively and thoroughly discussed and the existing results are reviewed according to the constraint types. Furthermore, some applications of the ADP method in practical systems are summarized. Finally, future topics are lighted on ADP-based control issues.