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Neural Computing and Applications
Published in: Neural Computing and Applications 17/2020

09-03-2020 | Original Article

Distributed fault-tolerant control of modular and reconfigurable robots with consideration of actuator saturation

Authors: Fan Zhou, Keping Liu, Yuanchun Li, Guangjun Liu

Published in: Neural Computing and Applications | Issue 17/2020

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Abstract

A novel decomposition-based distributed robust fault-tolerant control method is proposed for modular and reconfigurable robots based on joint torque sensing. The designed robust controller compensates for both model uncertainties and a class of actuator faults. In addition, the proposed scheme does not require a fault detection and diagnosis module, avoiding time delay associated with it. Furthermore, a radial basis function neural network-based compensation scheme is proposed to deal with the actuator saturation problem, which is especially critical when actuator fault has to be tolerated by the control system. Simulation results have shown the effectiveness of the presented method.
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Metadata
Title
Distributed fault-tolerant control of modular and reconfigurable robots with consideration of actuator saturation
Authors
Fan Zhou
Keping Liu
Yuanchun Li
Guangjun Liu
Publication date
09-03-2020
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 17/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-04768-z

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