The calcination zone temperature control is an important problem in rotary kiln production process. In order to solve this problem,a predictive control method based on improved harmony search algorithm( IHS)and least ...The calcination zone temperature control is an important problem in rotary kiln production process. In order to solve this problem,a predictive control method based on improved harmony search algorithm( IHS)and least square support vector machine( LSSVM) is proposed. LSSVM is utilized to bulid the nonlinear predictive model of calcination zone temperature in rotary kiln. The calcination zone temperature can be predicted through input control variable,the error and error correction of output feedback. The performance index function is established by deviation and control variable. An IHS algorithm with better fitness and faster convergence speed is proposed. The optimal control variable can be obtained by rolling optimization through this IHS algorithm. The stability of this predictive control method is proved to be feasible. The simulation and actual experiment results show that the proposed predictive control method has good control performance.展开更多
基金Sponsored by National Natural Science Foundation of China(Grant No.61433004)the Liaoning Province Doctor Startup Fund(Grant No.20141070)
文摘The calcination zone temperature control is an important problem in rotary kiln production process. In order to solve this problem,a predictive control method based on improved harmony search algorithm( IHS)and least square support vector machine( LSSVM) is proposed. LSSVM is utilized to bulid the nonlinear predictive model of calcination zone temperature in rotary kiln. The calcination zone temperature can be predicted through input control variable,the error and error correction of output feedback. The performance index function is established by deviation and control variable. An IHS algorithm with better fitness and faster convergence speed is proposed. The optimal control variable can be obtained by rolling optimization through this IHS algorithm. The stability of this predictive control method is proved to be feasible. The simulation and actual experiment results show that the proposed predictive control method has good control performance.
