Multi-Step Model Predictive Control Based on Online Support Vector Regression Optimized by Multi-Age

• 作 者: TANG Xianlun LIU Nianci WAN Yali GUO Fei
• 机 构: College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
• 出 处: 上海交通大学学报（英文版）
• 发表日期: 2018年5期
• 关键词: online support vector regression (OSVR) model predictive controller (MPC) multi-

As optimization of parameters affects prediction accuracy and generalization ability of support vector regression (SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a multi-step model predictive control based on online SVR (OSVR) optimized by multi-agent particle swarm optimization algorithm (MAPSO) is put forward.By integrating the online leing ability of OSVR,the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well.