Study of Generalized Predictive Control Scheme and Algorithm Based on Artificial Neural Network
Predictive control algorithm had been developed rapidly and successfully used in the industrial production practice from the 20th century 70s until now, and the Generalized Predictive Control (GPC) algorithm had been gotten well control effect to the linear or weak nonlinear systems. But there were still difficulties to construct many steps predictive models and its control rules for the strong nonlinear systems. For solved the questions, based on the high nonlinear mapping property of Artificial Neural Networks (ANN), the control structure scheme which was GPCs algorithm with the ANNs technologies was studied. The GPCs control structure scheme and its algorithm based on ANN for the nonlinear system were designed. The GPCs control principle, control algorithm and setting different parameters of the GPCs criterion function were analysed. Finally, simulation studies of the GPC control structure scheme and its algorithm based on the ANN have done for the nonlinear system. Simulation results show, the GPCs control structure scheme and its algorithm based on ANN were feasible and effective for nonlinear system.
Artificial Neural Networks (ANN) Nonlinear System Generalized Predictive Control (GPC) Simulation
Li Zhou Dongcai Qu
Math & Information College Ludong University Yantai, Shandong Province, 264025, P. R. China Department of Control Engineering Naval Aeronautical Engineering Institute Yantai, Shandong Province
国际会议
2006 IEEE International Conference on Information Acquisition
山东威海
英文
1208-1212
2006-08-20（万方平台首次上网日期，不代表论文的发表时间）