Improved Adaptive Dynamic Surface Control for a Class of Uncertain Nonlinear Systems

被引：0
|
作者：
Feng, Haoming [1 ]
Liu, Zongcheng [1 ]
Chen, Yong [1 ]
Zhang, Wenqian [1 ]
Zhou, Yang [1 ]
Wang, Long [1 ]
Li, Qiuni [1 ]
机构：
[1] Air Force Engn Univ, Aeronaut Engn Coll, Xian 710038, Peoples R China
来源：
IEEE ACCESS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
Neural networks; improved dynamic surface control (IDSC); strict-feedback nonlinear system; virtual control signal; OUTPUT-FEEDBACK CONTROL; FAULT-TOLERANT CONTROL; TIME-DELAY SYSTEMS; UNKNOWN DEAD ZONE; NEURAL-CONTROL; TRACKING CONTROL; CONTROL DESIGN; NETWORKS;
D O I：
10.1109/ACCESS.2020.3035757
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An improved dynamic surface control (IDSC) approach is presented for a class of strict-feedback nonlinear systems with unknown functions. The proposed method makes the state errors get rid of the influence of first-order filters, which simplifies the design of control. By employing neural networks to account for system uncertainties, the virtual control signal of the IDSC is directly used to construct the state error instead of the signal generated by the first-order filter in the dynamic surface control (DSC) method. The stability of the method is proved by Lyapunov stability theory, and the semi-global uniform ultimate boundedness of all signals in the closed-loop system is guaranteed. Simulation results demonstrate the IDSC method has better tracking performance and stability than traditional DSC method.
引用
收藏
页码：206174 / 206182
页数：9
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