Quantized Decentralized Adaptive Neural Network PI Tracking Control for Uncertain Interconnected Nonlinear Systems With Dynamic Uncertainties

被引：36
作者：
Sun, Haibin [1 ]
Zong, Guangdeng [1 ]
Ahn, Choon Ki [2 ]
机构：
[1] Qufu Normal Univ, Sch Engn, Rizhao 276826, Peoples R China
[2] Korea Univ, Sch Elect Engn, Seoul 136701, South Korea
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2021年 / 51卷 / 05期
基金：
新加坡国家研究基金会; 中国国家自然科学基金;
关键词：
Quantization (signal); Uncertainty; Neural networks; Interconnected systems; Nonlinear dynamical systems; Control systems; Decentralized control; input quantization; interconnected system; neural network-based control; nontriangular form; proportional– integral (PI) tracking controller; TIME-DELAY SYSTEMS; FEEDBACK-CONTROL; FUZZY CONTROL; STABILIZATION; DESIGN; REJECTION; SCHEME;
D O I：
10.1109/TSMC.2019.2918142
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a decentralized adaptive neural network proportional-integral (PI) tracking control scheme is proposed for interconnected nonlinear systems with input quantization and dynamic uncertainties. This algorithm is underpinned by the use of the dynamic signal, graph theory, and function recombination to deal with the difficulties existing in the nontriangular form, unmodeled dynamics, and unknown interconnected terms. Recalling the backstepping method and neural network approximation technology, a new PI tracking controller characterized by simple structure and easy implementation is developed which ensures that all the closed-loop signals are uniformly ultimately bounded. The effectiveness of the obtained controller is exemplified via a numerical example and an application to an inverted pendulum.
引用
收藏
页码：3111 / 3124
页数：14
相关论文
共 70 条
[1]  
Bergen A.R., 1986, Power System Analysis
[2]   Fuzzy Generalized H2 Filtering for Nonlinear Discrete-Time Systems With Measurement Quantization [J].
Chang, Xiao-Heng ;
Li, Zhi-Min ;
Park, Ju H. .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2018, 48 (12) :2419-2430
[3]   Novel adaptive neural control design for nonlinear MIMO time-delay systems [J].
Chen, Bing ;
Liu, Xiaoping ;
Liu, Kefu ;
Lin, Chong .
AUTOMATICA, 2009, 45 (06) :1554-1560
[4]   Direct adaptive fuzzy control of nonlinear strict-feedback systems [J].
Chen, Bing ;
Liu, Xiaoping ;
Liu, Kefu ;
Lin, Chong .
AUTOMATICA, 2009, 45 (06) :1530-1535
[5]   Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems [J].
Chen, C. L. Philip ;
Wen, Guo-Xing ;
Liu, Yan-Jun ;
Liu, Zhi .
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (07) :1591-1601
[6]   Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks [J].
Chen, C. L. Philip ;
Wen, Guo-Xing ;
Liu, Yan-Jun ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2014, 25 (06) :1217-1226
[7]   Decentralized output-feedback neural control for systems with unknown interconnections [J].
Chen, Weisheng ;
Li, Junmin .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2008, 38 (01) :258-266
[8]   New self-tuning fuzzy PI control of a novel doubly salient permanent-magnet motor drive [J].
Cheng, Ming ;
Sun, Qiang ;
Zhou, E. .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2006, 53 (03) :814-821
[9]   An Improved Analytical PID Controller Design for Non-Monotonic Phase LTI Systems [J].
de Paula, Caio F. ;
Ferreira, Luis H. C. .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2012, 20 (05) :1328-1333
[10]   TRACKING AND DISTURBANCE REJECTION OF MIMO NONLINEAR-SYSTEMS WITH PI CONTROLLER [J].
DESOER, CA ;
LIN, CA .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1985, 30 (09) :861-867
1234567