Low-Complexity Tracking Control of Strict-Feedback Systems With Unknown Control Directions

被引：162

作者：

Zhang, Jin-Xi ^{[1
]}

Yang, Guang-Hong ^{[1
,2
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China

[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Liaoning, Peoples R China

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2019年 / 64卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Switches; Transient analysis; Uncertainty; Nonlinear systems; Steady-state; Robustness; Low-complexity; nonlinear systems; prescribed performance; static control; unknown control directions; UNCERTAIN NONLINEAR-SYSTEMS; A-PRIORI KNOWLEDGE; COOPERATIVE OUTPUT REGULATION; ADAPTIVE NEURAL-CONTROL; ROBUST-CONTROL DESIGN; PRESCRIBED PERFORMANCE; MULTIAGENT SYSTEMS; LEARNING CONTROL; GLOBAL TRACKING; CONTROL SCHEME;

D O I：

10.1109/TAC.2019.2910738

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper focuses on the problem of output tracking with prescribed transient and steady-state performance for strict-feedback systems with unknown nonlinear functions and unmatched disturbances. In lieu of Nussbaum gain techniques, parameter estimation algorithms and switching control strategies, a continuous static low-complexity control solution is provided by means of a novel combination of smooth orientation functions and error transformation functions. The proposed method possesses inherent robustness against model uncertainties, disturbances, and virtual control signal derivatives, thus eliminating the needs to introduce extra robust control schemes and compute analytic derivatives. Comparative simulation results further illustrate the above theoretical findings.

引用

页码：5175 / 5182

页数：8

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