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Run-time efficient observer-based fuzzy-neural controller for nonaffine multivariable systems with dynamical uncertainties

机译:具有动态不确定性的非仿射多变量系统的基于运行时有效观察者的模糊神经控制器

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In this paper, a novel hierarchical structure with run-time efficiency is developed to solve the rule explosion problem of fuzzy neural network control for a class of uncertain nonaffine multivariable systems. The parameters of the hybrid adaptive controller are on-line tuned by the derived update laws under the constraint that only system outputs are available for measurement. Compared with the previous approaches, the proposed design process is more flexible and requires less computation time. According to the stability analysis, the overall control scheme guarantees that the closed-loop systems can obtain successful system control, effective state observer, and desired tracking performance. Finally, illustrative examples are provided to show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.
机译:为了解决一类不确定的非仿射多变量系统的模糊神经网络控制的规则爆炸问题,提出了一种具有运行时效率的新型分层结构。在仅系统输出可用于测量的约束下,通过派生的更新定律对混合自适应控制器的参数进行在线调整。与以前的方法相比,所提出的设计过程更加灵活并且需要更少的计算时间。根据稳定性分析,总体控制方案保证了闭环系统可以获得成功的系统控制,有效的状态观测器和所需的跟踪性能。最后,提供了示例,以说明所提出方法的有效性。 (C)2015 Elsevier B.V.保留所有权利。

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