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首页> 外文期刊>IEEE Transactions on Fuzzy Systems >Adaptive fuzzy H/sub /spl infin// stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach
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Adaptive fuzzy H/sub /spl infin// stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach

机译:通过反步和小增益方法对严格反馈规范非线性系统进行自适应模糊H / sub / spl infin //镇定

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摘要

A novel adaptive fuzzy controller with H/sub /spl infin// performance is proposed for a wide class of strict-feedback canonical nonlinear systems. The systems may possess a class of uncertainties referred to as unstructured uncertain functions, which are not linearly parameterized and have no prior knowledge of the bound. The Takagi-Sugeno-type fuzzy logic systems are used to approximate the uncertainties and a systematic design procedure is developed for synthesis of adaptive fuzzy control with H/sub /spl infin// performance, which combines the backstepping technique and generalized small gain approach. The method preserves the three advantages, those are, the semiglobal uniform ultimate bound of adaptive control in the presence of unstructured uncertainties can be guaranteed, the adaptive mechanism with only one learning parameter is obtained and the possible controller singularity problem in some of the existing adaptive control schemes with feedback linearization techniques can be removed. Performance and limitations of proposed method are discussed and illustrated with simulation results.
机译:针对广泛的严格反馈规范非线性系统,提出了一种具有H / sub / spl infin //性能的新型自适应模糊控制器。该系统可能具有一类不确定性,称为非结构化不确定性函数,这些不确定性未进行线性参数化并且对边界没有先验知识。使用Takagi-Sugeno型模糊逻辑系统来近似不确定性,并开发了一种具有H / sub / spl infin //性能的自适应模糊控制综合系统设计程序,该方法结合了Backstepping技术和广义小增益方法。该方法保留了三个优点,即,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半全局一致最终极限,可以得到仅具有一个学习参数的自适应机制,并且在某些现有的自适应算法中可能存在控制器奇异性问题。具有反馈线性化技术的控制方案可以删除。仿真结果讨论并说明了该方法的性能和局限性。

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