Title :
A Novel Robust Tuning Strategy for Model Predictive Control
Author :
Han, Kai ; Zhao, Jun ; Qian, Jixin
Author_Institution :
Inst. of Syst. Eng., Zhejiang Univ., Hangzhou
Abstract :
A novel and easy-to-use robust tuning strategy for model predictive control (MPC) is presented. The proposed strategy based on min-max algorithm can deal with model uncertainty explicitly; it could design an MPC controller with strong robustness and small overshooting, owing to the performance index employed in the strategy. Another contribution of the performance index is to avoid large prediction horizon and control horizon being selected to MPC controllers, which can reduce the MPC online computation. The superiority of the proposed robust tuning strategy has been demonstrated by simulation results
Keywords :
minimax techniques; performance index; predictive control; robust control; uncertain systems; control horizon; min-max algorithm; model predictive control; model uncertainty; online computation; performance index; prediction horizon; robust tuning; Algorithm design and analysis; Industrial control; Modeling; Performance analysis; Predictive control; Predictive models; Robust control; Robustness; Systems engineering and theory; Uncertainty; MPC; Min-Max optimization; PSO; autotuning; performance index;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714318