Adaptive fuzzy finite-time stability of uncertain nonlinear systems based on prescribed performance

被引：0
作者：
Liu, Yang [1 ,2 ]
Liu, Xiaoping [2 ]
Jing, Yuanwei [1 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Liaoning, Peoples R China
[2] Lakehead Univ, Dept Elect Engn, Thunder Bay, ON P7B 5E1, Canada
来源：
FUZZY SETS AND SYSTEMS | 2019年 / 374卷
基金：
加拿大自然科学与工程研究理事会;
关键词：
Finite-time stability; Prescribed performance control; Fuzzy logic systems; OUTPUT-FEEDBACK CONTROL; TRACKING CONTROL; MULTIAGENT SYSTEMS; NEURAL-NETWORKS; CONTROL DESIGN; STABILIZATION; SYNCHRONIZATION; MODEL;
D O I：
10.1016/j.fss.2018.12.0150165
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The semi-globally practical finite-time stability (SGPFS) problem for a class of uncertain strict-feedback nonlinear systems is discussed in this paper. A novel performance function called finite-time performance function (FTPF) is first defined. Moreover, this paper is the first to solve an adaptive semi-globally practical finite-time control issue by combining with backstepping, prescribed performance control (PPC) and fuzzy logic systems. Furthermore, it is proven that the designed control law not only guarantees that all the states converge to a predefined zone in finite-time, but also all the signals of the closed-loop systems are SGPF-stable. Simulation examples are worked out to illustrate the superiority and feasibility of the proposed design method. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：23 / 39
页数：17
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