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Nonlinear model predictive control based on support vector machine and genetic algorithm 被引量:5
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作者 冯凯 卢建刚 陈金水 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期2048-2052,共5页
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ... This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection. 展开更多
关键词 support vector machine genetic algorithm Nonlinear model predictive control Neural network modeling
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