NONLINEAR SYSTEM MULTI-STEP PREDICTIVE CONTROL BASED NEURAL NETWORK MODEL AND GENETIC ALGORITHM

摘要：

A nonlinear multi-step predictive control strategy using Radial Basis Function Neural Network (RBFNN) as multi-step predictive model for nonlinear complicated industrialized process with time delay, slow time variety and highly disturbance is proposed in the paper.The modified elitist preserved genetic algorithm is used to obtain the online nonlinear optimization.Simulation results demonstrate that the strategy has good robustness and the resisting time variety ability.

关键词： Modified preserved elitist genetic algorithm Radial Basis Function Neural Network nonlinear predictive control robustness time delay

作者: CHEN HONG VAN

作者单位: School of Electrical Engineering and Automation Tianjin Polytechnic University

会议类型: 国际会议

会议名称: 3rd International Conference on Mechanical and Electrical Technology(ICMET2011) (2011第三届机械与电气技术国际会议)

会议地点: 大连

会议语种:英文

页码: 227-231

在线出版日期: 2011-08-26（万方平台首次上网日期，不代表论文的发表时间）