Thruster Fault-Tolerant for UUVs Based on Quantum-Behaved Particle Swarm Optimization

Abstract

The thruster fault-tolerant approach for Unmanned Underwater Vehicles (UUV) using Quantum-behaved Particle Swarm Optimization (QPSO) is presented in this paper. The QPSO algorithm is a new global convergent stochastic search technique, which is inspired by the fundamental theory of Particle Swarm Optimization (PSO) and quantum mechanics. The corresponding weighting matrix for faulty situations is developed with the faults of the thruster detected, and the QPSO is used to find the solution of the control reallocation problem, which minimizes the control energy cost function. Comparing with the method of the weighted pseudo-inverse, QPSO algorithm does not need truncation or scaling to ensure the feasibility of the solution because its particles search the solution in the feasible space. Both the magnitude error and direction error of the obtained control input vector using QPSO algorithm are equal to zero. The experimental results demonstrate that the proposed scheme based on QPSO algorithm performs an appropriate control reconfiguration.