A brief survey on nonlinear control using adaptive dynamic programming under engineering-oriented complexities

Abstract

Nonlinear dynamics is frequently encountered in practical applications. Adaptive dynamic programming (ADP), which is implemented via actor/critic neural networks with excellent approximation capabilities, is appropriate to be used in finding the solution for the control problem in the presence of known/unknown nonlinear dynamics. The objective of this paper is to introduce state-of-the-art ADP-based algorithms and survey the recent advances in the ADP-based control strategies for nonlinear systems with various engineering-oriented complexities. Firstly, the main motivation of the ADP-based algorithms is thoroughly discussed, and the way of implementing the ADP-based algorithms is highlighted. Then, the latest research results concerning ADP-based control policy design for nonlinear systems are reviewed in detail, Finally, we conclude the survey by outlining the challenges and possible research topics in the future.