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Robustly stabilising model predictive control design for networked control systems with an application to direct current motors

机译:网络控制系统的鲁棒稳定模型预测控制设计及其在直流电动机上的应用

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摘要

In networked control systems there are many network-induced imperfections and constraints: quantisation errors, packet dropouts, variable sampling periods, time-varying delays and communication constraints. The goal of this study is to provide a control design methodology that can assure the closed-loop performances of a network-controlled application, while compensating the time-varying delays introduced by the communication network. To this end, firstly, the error caused by the time-varying delays is modelled as a disturbance and a novel method of bounding the disturbances is proposed. Secondly, an one-step ahead predictive controller based on flexible control Lyapunov functions is designed, which explicitly takes into account the bounds of the disturbances caused by time-varying delays and guarantees also the input-to-state stability of the system. The methodology is then applied for a network-controlled direct current (DC) motor and the TrueTime simulations illustrate the effectiveness and robustness of the proposed delay modelling and control strategy.
机译:在网络控制系统中,存在许多由网络引起的缺陷和约束:量化误差,数据包丢失,可变采样周期,时变延迟和通信约束。这项研究的目的是提供一种控制设计方法,该方法可以确保网络控制的应用程序的闭环性能,同时补偿通信网络引入的时变延迟。为此,首先,将由时变延迟引起的误差建模为扰动,并提出了一种新的界定扰动的方法。其次,设计了一种基于柔性控制李雅普诺夫函数的单步超前预测控制器,该控制器明确考虑了时变时延引起的干扰范围,并保证了系统的输入状态稳定性。然后将该方法应用于网络控制的直流(DC)电动机,TrueTime仿真说明了所提出的延迟建模和控制策略的有效性和鲁棒性。

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