Adaptive Model Predictive Control for Linear Systems with Parametric Uncertainties and Time Delay
KONG Lingren1, QI Qingyuan2
1. Institute of Complexity Science, Qingdao University, Qingdao 266071, China; 2. Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266000, China
Abstract：This paper investigates the adaptive model predictive control (MPC) for a class of constrained linear multiple-input multiple-output (MIMO) systems with parametric uncertainty and input delay. An adaptive update law based on time-varying updating rate is proposed, which enables the update of uncertain parameters in the presence of input delay. Consequently, to deal with the constraints, we convert the optimization problem into a solvable simple structure, which originates from the min-max optimization. Furthermore, theoretically, it is shown that the closed-loop system is asymptotically stable and the proposed adaptive MPC strategy is proved to be recursively feasible. Finally, numerical simulation is given to illustrate the efficacy of the proposed method.
孔令仁, 亓庆源. 含参数不确定及时滞的线性系统自适应模型预测控制[J]. 复杂系统与复杂性科学, 2024, 21(3): 136-143.
KONG Lingren, QI Qingyuan. Adaptive Model Predictive Control for Linear Systems with Parametric Uncertainties and Time Delay[J]. Complex Systems and Complexity Science, 2024, 21(3): 136-143.
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