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The Scientific World Journal
Volume 2013, Article ID 907256, 8 pages
http://dx.doi.org/10.1155/2013/907256
Research Article

Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System

1School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210014, China
2Research Institute, North Heavy Industries Group Corp. LTD, Inner Mongolia, Baotou 014033, China

Received 30 March 2013; Accepted 8 May 2013

Academic Editors: J. P. S. Catalão and P. Lonetti

Copyright © 2013 Qiang Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.