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Quantum-Behaved Particle Swarm Optimization Fault-Tolerant Control for Human Occupied Vehicle

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Intelligent Robotics and Applications (ICIRA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13016))

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Abstract

In this paper, for the human occupied vehicle (HOV) system, the control strategies are used to reallocate the thruster forces based on quantum-behaved particle swarm optimization (QPSO). QPSO is adopted in terms of the solution quality, robustness and the convergence property. When the normalized thruster forces are out of maximum limits, the QPSO is used for the restricted usage of the faulty thruster and to find the solution of the control reallocation problem within the limits. An optimization criterion with the infinite norm as the cost function is introduced into the QPSO algorithm accelerate the search for the optimal solution in the feasibility space so as to ensure the feasibility of the solution. To show the efficiency of QPSO fault-tolerant control, GA, PSO and pseudo inverse method were conducted to study the proposed fault-tolerant control method. Experimental results showed the proposed fault-tolerant method could reallocate the thruster forces effective after thruster fault.

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Correspondence to Daqi Zhu .

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Zhang, H., Zhu, D. (2021). Quantum-Behaved Particle Swarm Optimization Fault-Tolerant Control for Human Occupied Vehicle. In: Liu, XJ., Nie, Z., Yu, J., Xie, F., Song, R. (eds) Intelligent Robotics and Applications. ICIRA 2021. Lecture Notes in Computer Science(), vol 13016. Springer, Cham. https://doi.org/10.1007/978-3-030-89092-6_57

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  • DOI: https://doi.org/10.1007/978-3-030-89092-6_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89091-9

  • Online ISBN: 978-3-030-89092-6

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