Compensator-based approximate optimal control for affine nonlinear systems with input constraints and unmatched disturbances

Ke Lu, Chunsheng Liu*, Jingliang Sun, Chunhua Li, Chengcheng Ma

*此作品的通讯作者

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3 引用 (Scopus)

摘要

This paper develops a novel approximate optimal control method for a class of constrained continuous-time nonlinear systems in the presence of disturbances via adaptive dynamic programming (ADP) technique. First, an auxiliary dynamic compensator is introduced to deal with the input constraints. Through augmenting the original system with the designed auxiliary compensator, the design of constrained optimal controller is circumvented by stabilizing the equivalent augmented system. Then, the cost function is appropriately redefined by introducing an additional function connected with disturbances for the augmented nominal system in order to compensate the effect of unmatched disturbances. Next, the solution of associated Hamilton-Jacobi-Bellman (HJB) equation is solved online with weight adaptation law using neural networks (NNs). Furthermore, an additional robustifying term is utilized to compensate the effect of the approximation error of NNs, and thus the asymptotic stability of the closed-loop system is guaranteed. Finally, all signals of the closed-loop system are proved to be asymptotic convergence by using Lyapunov method. Simulation examples demonstrate the effectiveness of the proposed scheme.

源语言英语
页(从-至)3024-3034
页数11
期刊Transactions of the Institute of Measurement and Control
42
15
DOI
出版状态已出版 - 1 11月 2020

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