Introducing robustness in model predictive control with multiple models and switching  

作　　者：Sachin PRABHU Koshy GEORG 

机构地区：[1]Department of Telecommunication Engineering,PES Institute of Technology, Bangalore 560085, India [2]PES Centre for Intelligent Systems,Bangalore 560085, IndiaE

出　　处：《Control Theory and Technology》2014年第3期284-303,共20页控制理论与技术（英文版）

摘　　要：Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.

关 键 词：Receding horizon control Time-varying horizon Multiple models SWITCHING TRACKING ROBUSTNESS 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]