Nonsingular Practical Fixed-Time Adaptive Output Feedback Control of MIMO Nonlinear Systems

Hao Xu, Dengxiu Yu, Shuai Sui, Yin Ping Zhao, C. L.Philip Chen, Zhen Wang

Research output: Contribution to journalArticlepeer-review

67 Scopus citations

Abstract

This article studies the nonsingular fixed-time control problem of multiple-input multiple-output (MIMO) nonlinear systems with unmeasured states for the first time. A state observer is designed to solve the problem that system states cannot be measured. Due to the existence of the unknown system nonlinear dynamics, neural networks (NNs) are introduced to approximate them. Then, through the combination of adaptive backstepping recursive technology and adding power integration technology, a nonsingular fixed-time adaptive output feedback control algorithm is proposed, which introduces a filter to avoid the complicated derivation process of the virtual control function. According to the fixed-time Lyapunov stability theory, the practical fixed-time stability of the closed-loop system is proven, which means that all signals of the closed-loop system remain bounded in a fixed time under the proposed algorithm. Finally, the effectiveness of the proposed algorithm is verified by the numerical simulation and practical simulation.

Original languageEnglish
Pages (from-to)7222-7234
Number of pages13
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume34
Issue number10
DOIs
StatePublished - 1 Oct 2023

Keywords

  • Adding power integration technology
  • fixed-time control
  • neural network (NN) adaptive control
  • nonsingular control
  • output feedback control

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