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Adaptive tube-based model predictive control for linear systems with parametric uncertainty

机译:具有参数不确定性的线性系统的基于管的自适应模型预测控制

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摘要

A tube-based robust model predictive control (MPC) is proposed to be applied in constrained linear systems with parametric uncertainty. An estimation method is applied in this proposed technique to adapt the system model at each sampling time and to reduce the conservatism nature of the tube-based MPC as the system model approaches the real model as time passes. By updating the subject model online through this newly proposed approach the performance of the system is improved. Asymptotic stability of the closed-loop system is established. The simulation results of a DC motor are applied to illustrate the effectiveness of this proposed controller in dealing with one practical system.
机译:提出了一种基于管的鲁棒模型预测控制(MPC)应用于具有参数不确定性的约束线性系统。在该提议的技术中应用了一种估计方法,以在每个采样时间适应系统模型,并随着时间的流逝,随着基于系统的模型逼近真实模型,降低基于管的MPC的保守性。通过使用这种新提出的方法在线更新主题模型,可以提高系统的性能。建立了闭环系统的渐近稳定性。直流电动机的仿真结果用于说明该控制器在处理一个实际系统中的有效性。

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