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Research on RBF Fuzzy Controller Based on Genetic Algorithm for Explosive Mine Sweeper

CHEN Ji-lin,WANG Li,GAO Qiang(School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China)  
Research the control for an explosive mine sweeper electro-hydraulic servo system.Due to the nonlinearities of hydraulic system and the variation of load and moment of inertia caused by the variation of launcher position and ammunitions,the construction method cannot achieve the satisfactory results.By analyzing the transfer function,a RBF neural network(RBFNN) fuzzy controller with its node centers and weights optimized by genetic algorithm(GA) was proposed.The control output in the index performance was squared to enhance its influence.The simulation results show that the designed controller has fast dynamic response and small overshoot under the variation of load and moment of inertia.
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