Adaptive prescribed-time consensus protocol design for multiple mechanical systems with actuator faults and output constraints

In this article, an adaptive prescribed-time consensus protocol is proposed for uncertain nonlinear multiple mechanical systems with actuator faults and time-varying asymmetric output constraints. Firstly, a designed nonlinear mapping function is used to deal with the output constrained system. And an unconstrained transformed system can be obtained. Then the radial basis function neural network is used to estimate the unknown nonlinear function, and the actuator fault is also taken into consideration. Combining with the prescribed-time control theory, it is proved that the position error and velocity error of the multiple mechanical systems can reach a certain area within prescribed time. Finally, the effectiveness of the protocol is verified through Matlab simulation.

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Published
2025-05-09
DOI
https://doi.org/10.1109/ddcls66240.2025.11065529
Primary Topic
Iterative Learning Control Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Adaptive prescribed-time consensus protocol design for multiple mechanical systems with actuator faults and output constraints

Yuming Li, Zhihao Xu, Zhaoyang Liao, Xuefeng Zhou
Iterative Learning Control Systems
article

Adaptive prescribed-time consensus protocol design for multiple mechanical systems with actuator faults and output constraints

Yuming Li, Zhihao Xu, Zhaoyang Liao, Xuefeng Zhou
article en

Abstract

In this article, an adaptive prescribed-time consensus protocol is proposed for uncertain nonlinear multiple mechanical systems with actuator faults and time-varying asymmetric output constraints. Firstly, a designed nonlinear mapping function is used to deal with the output constrained system. And an unconstrained transformed system can be obtained. Then the radial basis function neural network is used to estimate the unknown nonlinear function, and the actuator fault is also taken into consideration. Combining with the prescribed-time control theory, it is proved that the position error and velocity error of the multiple mechanical systems can reach a certain area within prescribed time. Finally, the effectiveness of the protocol is verified through Matlab simulation.

Guangdong Institute of Intelligent Manufacturing (CN)
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Iterative Learning Control Systems
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