Nonsingular Fixed‐Time Terminal Sliding Mode Control Based Emotional Neural Network for Nonlinear Systems

ABSTRACT A fixed‐time nonsingular terminal sliding mode control (TSMC) method based on emotional neural network (ENN) is proposed for nonlinear systems. First of all, a new terminal sliding surface (TSS) is proposed in this article, which can adaptively adjust when the system states are far and near the origin and achieve fixed time fast convergence. Second, the equivalent control term in the controller is approximated by the ENN, which solves the singularity problem of traditional TSMC and the problem of unknown model information simultaneously. Finally, by using Lyapunov stability theorem, it is proved that the system states are stable in a fixed time during both sliding and reaching stages, which is independent of the initial values. The proposed method is verified and compared on an inverted pendulum system, which shows a better control performance.

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Institutions

Publication Details

Journal
International Journal of Adaptive Control and Signal Processing
Published
2024-12-30
DOI
https://doi.org/10.1002/acs.3965
Citations
2
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
0.66

Funders

Controls
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article

Nonsingular Fixed‐Time Terminal Sliding Mode Control Based Emotional Neural Network for Nonlinear Systems

Chao Jia, Xiaohua Liu
2 citations
International Journal of Adaptive Control and Signal Processing
Adaptive Control of Nonlinear Systems
0.66
article

Nonsingular Fixed‐Time Terminal Sliding Mode Control Based Emotional Neural Network for Nonlinear Systems

Chao Jia, Xiaohua Liu
article en
2 citations

Abstract

ABSTRACT A fixed‐time nonsingular terminal sliding mode control (TSMC) method based on emotional neural network (ENN) is proposed for nonlinear systems. First of all, a new terminal sliding surface (TSS) is proposed in this article, which can adaptively adjust when the system states are far and near the origin and achieve fixed time fast convergence. Second, the equivalent control term in the controller is approximated by the ENN, which solves the singularity problem of traditional TSMC and the problem of unknown model information simultaneously. Finally, by using Lyapunov stability theorem, it is proved that the system states are stable in a fixed time during both sliding and reaching stages, which is independent of the initial values. The proposed method is verified and compared on an inverted pendulum system, which shows a better control performance.

International Journal of Adaptive Control and Signal ProcessingVol. 39(4)
Tianjin University of Science and Technology (CN), Tianjin University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Tianjin City
Openalex Percentile: Top 28%
Adaptive Control of Nonlinear Systems
0.66
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Nonsingular Fixed‐Time Terminal Sliding Mode Control Based Emotional Neural Network for Nonlinear Systems — Chao Jia, Xiaohua Liu · International Journal of Adaptive Control and Signal Processing (2024) | TGRS Research Map | TGRS