Unmanned Underwater Vehicles Fault Identification and Fault-Tolerant Control Method Based on FCA-CMAC Neural Networks, Applied on an Actuated Vehicle

Authors:
Qian Liu;Daqi Zhu;Simon X. Yang
Affiliations:
Laboratory of Underwater Vehicles and Intelligent Systems, Shanghai Maritime University, Shanghai, China 200135;Laboratory of Underwater Vehicles and Intelligent Systems, Shanghai Maritime University, Shanghai, China 200135 and Advanced Robotics and Intelligent Systems Laboratory, School of Engineering, Uni ...;Advanced Robotics and Intelligent Systems Laboratory, School of Engineering, University of Guelph, Guelph, Canada N1G2W1
Venue:
Journal of Intelligent and Robotic Systems
Year:
2012

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Abstract

A novel fault diagnosis and accommodation method for unmanned underwater vehicles thruster is presented in this paper. FCA-CMAC (Credit Assignment-based Fuzzy Cerebellar Model Articulation Controllers) neural network is used to realize the fault identification for thruster continuous and uncertain jammed fault situation. A reconstruction algorithm based on weighted pseudo-inverse is used to find the available solution of the control allocation problem. To illustrate effective of the proposed method, two simulation examples of multi-uncertain abrupt faults are given in the paper.