基于支持向量机和遗传算法的非线性模型预测控制（英文）

• 作 者: 冯凯 卢建刚 陈金水
• 机 构: State Key Laboratory of Industrial Control Technology,College of Control Science and Engineering,Zhe
• 出 处: Chinese Journal of Chemical Engineering
• 发表日期: 2015年12期
• 关键词: 模型预测控制 遗传算法 disturbance rejection elite 支持向量机 preserve predictive crossover inst

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.

This paper presents a nonlinear model predictive control (NMPC) approach based on support vector machine (SVM) and genetic algorithm (GA) for multiple-output multiple-output 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.