Online H∞ control for completely unknown nonlinear systems via an identifier–critic-based ADP structure

Yongfeng Lv, Jing Na*, Xuemei Ren

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

36 引用 (Scopus)

摘要

In this paper, we propose an identifier–critic-based approximate dynamic programming (ADP) structure to online solve H∞ control problem of nonlinear continuous-time systems without knowing precise system dynamics, where the actor neural network (NN) that has been widely used in the standard ADP learning structure is avoided. We first use an identifier NN to approximate the completely unknown nonlinear system dynamics and disturbances. Then, another critic NN is proposed to approximate the solution of the induced optimal equation. The H∞ control pair is obtained by using the proposed identifier–critic ADP structure. A recently developed adaptation algorithm is used to online directly estimate the unknown NN weights simultaneously, where the convergence to the optimal solution can be rigorously guaranteed, and the stability of the closed-loop system is analysed. Thus, this new ADP scheme can improve the computational efficiency of H∞ control implementation. Finally, simulation results confirm the effectiveness of the proposed methods.

源语言英语
页(从-至)100-111
页数12
期刊International Journal of Control
92
1
DOI
出版状态已出版 - 2 1月 2019

指纹

探究 'Online H∞ control for completely unknown nonlinear systems via an identifier–critic-based ADP structure' 的科研主题。它们共同构成独一无二的指纹。

引用此

Lv, Y., Na, J., & Ren, X. (2019). Online H∞ control for completely unknown nonlinear systems via an identifier–critic-based ADP structure. International Journal of Control, 92(1), 100-111. https://doi.org/10.1080/00207179.2017.1381763