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IMPROVED MULTIPLE MODEL ADAPTIVE CONTROL AND ITS STABILITY ANALYSIS

机译:改进的多模型自适应控制及其稳定性分析

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摘要

Multiple model adaptive control (MMAC) of discrete time plant is considered in this paper. The plant can be a time invariant system with unknown parameters or a time variant system with jumping parameter. Localization method is combined with the design of discrete time system MMAC. Multiple models of the plant are set up to cover the uncertainties of the plant dynamics. Every sample time, by using localization method, only a few of models which are closer to the "true" model of the plant are selected to form a multiple model controller, so the big computation burden of the multiple model algorithm is greatly reduced. It is proved that the closed-loop system is stable when multi-model controller is used to a linear time-invariant plant with unknown parameters. The simulation results are given to show the usefulness of the proposed method.
机译:本文考虑了离散时间工厂的多模型自适应控制(MMAC)。植物可以是参数未知的时不变系统,也可以是参数跳跃的时变系统。定位方法与离散时间系统MMAC的设计相结合。建立了多种工厂模型来覆盖工厂动态的不确定性。在每个采样时间,通过使用定位方法,仅选择一些更接近工厂“真实”模型的模型来形成多模型控制器,因此大大减轻了多模型算法的巨大计算负担。实践证明,当多模型控制器用于参数未知的线性时不变设备时,闭环系统是稳定的。仿真结果表明了该方法的有效性。

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