Decentralized Dynamic Event-Triggered Output Feedback Adaptive Fixed-Time Funnel Control for Interconnection Nonlinear systems

被引：9
作者：
Sun, Haibin [1 ]
Hou, Linlin [2 ]
Wei, Yunliang [3 ]
机构：
[1] Qufu Normal Univ, Sch Engn, Rizhao 276826, Shandong, Peoples R China
[2] Qufu Normal Univ, Sch Informat Sci & Engn, Rizhao 276826, Shandong, Peoples R China
[3] Qufu Normal Univ, Sch Math Sci, Qufu 273165, Shandong, Peoples R China
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2024年 / 35卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Nonlinear systems; Adaptive systems; Sun; Output feedback; Observers; Stability criteria; Learning systems; Decentralized control; event-triggered control (ETC); fixed-time (FxT) control; funnel control; interconnected nonlinear system (INS); neural network (NN); output feedback; TRACKING CONTROL; CONSENSUS TRACKING; DELAY SYSTEMS; STABILIZATION; DESIGN;
D O I：
10.1109/TNNLS.2022.3183290
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A decentralized dynamic event-triggered output feedback adaptive fixed-time (DDETOFAFxT) funnel controller is described for a class of interconnected nonlinear systems (INSs). A novel dynamic event-triggered mechanism is designed, which includes a triggering control input, fixed threshold, decreasing function of tracking error, and a dynamic variable. To obtain the unknown states, a decentralized linear filter is designed. By introducing a prescribed funnel and using an adding a power integrator technique and a neural network method, a DDETOFAFxT funnel controller is designed to obtain better tracking performance and effectively alleviate the computational burden. Furthermore, it is ensured that the tracking error falls into a preset performance funnel. A simulation example is presented to demonstrate the availability of the designed control scheme.
引用
收藏
页码：1364 / 1378
页数：15
相关论文
共 66 条
[31]   Nonlinear Feedback Design for Fixed-Time Stabilization of Linear Control Systems [J].
Polyakov, Andrey .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (08) :2106-U1
[32]   A continuous feedback approach to global strong stabilization of nonlinear systems [J].
Qian, CJ ;
Lin, W .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2001, 46 (07) :1061-1079
[33]   Asynchronous Finite-Time Filtering of Networked Switched Systems and Its Application: An Event-Driven Method [J].
Ren, Hangli ;
Zong, Guangdeng ;
Karimi, Hamid Reza .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2019, 66 (01) :391-402
[34]   Decentralized adaptive control of nonlinear systems using radial basis neural networks [J].
Spooner, JT ;
Passino, KM .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1999, 44 (11) :2050-2057
[35]   Command filter-based event-triggered adaptive fixed-time output-feedback control for large-scale nonlinear systems [J].
Su, Yuanbo ;
Xue, Hong ;
Wang, Yan ;
Pan, Yingnan .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2021, 52 (15) :3190-3205
[36]   Adaptive decentralized finite-time tracking control for uncertain interconnected nonlinear systems with input quantization [J].
Sun, Haibin ;
Hou, Linlin .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2021, 31 (10) :4491-4510
[37]   Adaptive decentralized output feedback PI tracking control design for uncertain interconnected nonlinear systems with input quantization [J].
Sun, Haibin ;
Zong, Guangdeng ;
Chen, C. L. Philip .
INFORMATION SCIENCES, 2020, 512 :186-206
[38]   Fixed-Time Attitude Tracking Control for Spacecraft With Input Quantization [J].
Sun, Haibin ;
Hou, Linlin ;
Zong, Guangdeng ;
Yu, Xinghuo .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2019, 55 (01) :124-134
[39]   Quantized Decentralized Adaptive Neural Network PI Tracking Control for Uncertain Interconnected Nonlinear Systems With Dynamic Uncertainties [J].
Sun, Haibin ;
Zong, Guangdeng ;
Ahn, Choon Ki .
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (05) :3111-3124
[40]   Adaptive Decentralized Neural Network Tracking Control for Uncertain Interconnected Nonlinear Systems With Input Quantization and Time Delay [J].
Sun, Haibin ;
Hou, Linlin ;
Zong, Guangdeng ;
Yu, Xinghuo .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (04) :1401-1409
1234567