Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (6): 1429-1431.

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Steady-state objective optimization in model predictive control and its application

WANG Bai-ping1, LI Shao-yuan1, ZOU Tao2   

  1. 1. Inst. of Automation, Shanghai Jiaotong Univ., Shanghai 200240, China;
    2. Inst. of Information and Control, Zhejiang Univ. of Technology, Hangzhou 310032, China
  • Received:2008-03-20 Revised:2008-05-30 Online:2009-06-20 Published:2010-01-03

Abstract: In the process of industry,the existence of process limitation or constraints and unavoidable model mismatch and disturbance may perturb the plant from the desired target,which will lead to steady state offset.MPC calculation is separated into steady-state and dynamic optimization.Considering the effects of measured disturbance,the steady-state objective is recalculated at each sampling time.The difference between the model prediction and the measured output at the current time is introduced into the model to incorporate feedback and the velocity constraints in steady-state target calculation so as to ensure the steady-state objective is compatible with the velocity constraints in dynamic MPC optimization.Finally,this control strategy is successfully applied to the control of the Shell heavy oil fractionators benchmark problem.

CLC Number: 

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