Identification and nonlinear model predictive control of MIMO Hammerstein system with constraints

• 作 者: LI Da-zi JIA Yuan-xin LI Quan-shan JIN Qi-bing
• 机 构: Department of Automation, Beijing University of Chemical Technology, Beijing 100029, China;Beijing C
• 出 处: 中南大学学报（英文版）
• 发表日期: 2017年2期
• 关键词: model predictive control system identification constrained systems Hammerstein m

This work is conced with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints.Firstly,an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system.A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model.Next,a computationally efficient nonlinear model predictive control algorithm (MGPC) is developed to deal with constrained problem of MIMO system.The identification process and performance of MGPC are shown.Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.