Direct adaptive self-structuring fuzzy control with interpretable fuzzy rules for a class of nonlinear uncertain systems

被引：24
|
作者：
Wang, Ning [1 ]
Sun, Jing-Chao [1 ,2 ]
Liu, Yan-Cheng [1 ]
机构：
[1] Dalian Maritime Univ, Marine Engn Coll, Dalian 116026, Peoples R China
[2] China CNR Corp Ltd, Dalian Elect Tract R&D Ctr, Dalian 116022, Peoples R China
来源：
NEUROCOMPUTING | 2016年 / 173卷
基金：
中国博士后科学基金;
关键词：
Direct adaptive control; Self-structuring fuzzy control; Interpretable fuzzy system; Nonlinear uncertain systems; ORGANIZING SCHEME; NEURAL-NETWORKS; MANIPULATORS;
D O I：
10.1016/j.neucom.2015.09.036
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a direct adaptive self-structuring fuzzy control (DASFC) scheme is proposed for tracking a class of nonlinear uncertain systems. In the DASFC, the ideal control law with unknown dynamics and uncertainties is approximated by a self-structuring interpretable fuzzy system (SIFS) which can automatically self-construct transparent fuzzy rules together with interpretable fuzzy sets projected in each dimension. Moreover, adaptive approximation error compensation and projection-based adaptive laws for all free parameters not only to address the robustness issue due to the SIFS-based approximation error, but also to guarantee globally asymptotical stability of the overall DASFC control system. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码：1640 / 1645
页数：6
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