Work

Optimal fault-tolerant control of modular manipulators based on hybrid triggering mechanism

Year: 2025

Type: article

Abstract: This paper proposes a fault tolerant control method based on a hybrid mechanismcombining event-triggered and time-triggered strategies for modular manipulators.By setting the threshold, this method enables intelligent switching betweentriggering modes when the threshold is reached, ensures trajectory tracking performance,reduces communication load, and improves fault tolerance accuracy.Furthermore, an adaptive fault observer is designed for effectively estimatingfaults in real time. The adaptive dynamic programming (ADP) algorithm transformsthe fault tolerant control problem into an optimal control problem and theHamilton-Jacobi-Bellman (HJB) equation is solved by the critic neural network(NN) to generate an approximate optimal fault tolerant control strategy. TheLyapunov stability theory verifies that the trajectory tracking error of the closedloopsystem is uniformly ultimately bounded (UUB) despite the occurrence ofactuator faults. Finally, the effectiveness and reliability of the proposed methodare confirmed using the experimental platform.

Source: Results in Engineering

DOI: 10.1016/j.rineng.2025.108014

Authors: Fan Zhou, YiFan Zhang, Haowei Chen

Institution: Changchun University of Technology

Language: English

Topic: Adaptive Dynamic Programming Control

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,940

Funders: National Natural Science Foundation of China, Heilongjiang Provincial Science and Technology Department, Department of Science and Technology of Jilin Province