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首页> 外文期刊>International journal of general systems >Robust adaptive fuzzy VSS control for a class of uncertain nonlinear systems using small gain design
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Robust adaptive fuzzy VSS control for a class of uncertain nonlinear systems using small gain design

机译:基于小增益设计的一类不确定非线性系统的鲁棒自适应模糊VSS控制。

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In this paper, a novel robust adaptive fuzzy variable structure control (RAFVSC) scheme is proposed for a class of uncertain nonlinear systems. The uncertain nonlinear system and gain functions originating from modeling errors and external disturbances are all unstructured (or non-repeatable), state-dependent and completely unknown. The Takagi-Sugeno type fuzzy logic systems are used to approximate uncertain functions in the systems and the RAFVSC is designed by use of the input-to-state stability (ISS) approach and small gain theorem. In the algorithm, there are three advantages which are that the asymptotic stability of adaptive control in the presence of unstructured uncertainties can be guaranteed, the possible controller singularity problem in some of existing adaptive control schemes using feedback linearization techniques can be removed and the adaptive mechanism with minimal learning parameterizations can be achieved. The performance and effectiveness of the proposed methods are discussed and illustrated with two simulation examples.
机译:针对一类不确定的非线性系统,提出了一种新颖的鲁棒自适应模糊变结构控制(RAFVSC)方案。源自建模误差和外部干扰的不确定非线性系统和增益函数都是非结构化的(或不可重复的),与状态有关且完全未知。 Takagi-Sugeno型模糊逻辑系统用于逼近系统中的不确定函数,RAFVSC通过使用输入到状态稳定性(ISS)方法和小增益定理进行设计。该算法具有三个优点:可以保证在存在非结构性不确定性的情况下自适应控制的渐近稳定性,可以消除使用反馈线性化技术的某些现有自适应控制方案中可能存在的控制器奇异性问题,并且可以采用自适应机制使用最少的学习参数化就可以实现。通过两个仿真实例对所提方法的性能和有效性进行了讨论和说明。

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