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BDI Agent and QPSO-based Parameter Optimization for a Marine Generator Excitation Controller

Wei Zhang1, Weifeng Shi2, Bing Sun3

1 Department of Electrical Engineering and Automation, Shanghai Dianji University, Shanghai, 201306, China
2 Department of Electrical Engineering and Automation, Shanghai Maritime University, Shanghai, 201306, China
3 Laboratory of Underwater Vehicles and Intelligent Systems, Shanghai Maritime University, Shanghai, 201306, China

* Corresponding Author: Wei Zhang, email

Intelligent Automation & Soft Computing 2019, 25(3), 423-431. https://doi.org/10.31209/2018.100000045

Abstract

An intelligent optimization algorithm for a marine generator excitation controller is proposed to improve dynamic performance of shipboard power systems. This algorithm combines a belief–desire–intention agent with a quantum-behaved particle swarm optimization (QPSO) algorithm to optimize a marine generator excitation controller. The shipboard zonal power system is simulated under disturbance due to load change or severe fault. The results show that the proposed optimization algorithm can improve marine generator stability compared with conventional excitation controllers under various operating conditions. Moreover, the proposed intelligent algorithm is highly robust because its performance is insensitive to the accuracy of system parameters.

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Cite This Article

W. Zhang, W. Shi and B. Sun, "Bdi agent and qpso-based parameter optimization for a marine generator excitation controller," Intelligent Automation & Soft Computing, vol. 25, no.3, pp. 423–431, 2019.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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