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An indirect model reference adaptive fuzzy control for SISO Takagi-Sugeno model

机译：SISO Takagi-Sugeno模型的间接模型参考自适应模糊控制

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摘要

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured state with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, an indirect model reference adaptive fuzzy control (MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.
机译：在本文中，为植物模型开发了一个参数估计器，该模型的结构由Takagi-Sugeno模型表示。在线估计背后的基本思想是将测量状态与结构与参数化模型相同的估计模型的状态进行比较。基于参数估计方案，提出了一种间接模型参考自适应模糊控制（MRAFC）方案，为参数不确定或时变缓慢的系统提供参考信号的渐近跟踪。发达的控制律和自适应律保证了闭环系统中所有信号的有界性。此外，对于任何有界参考输入信号，工厂状态都会随着时间渐近跟踪参考模型的状态。

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