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Robust self-learning fuzzy logic controller for a class of nonlinear MIMO systems

机译:一类非线性MIMO系统的强大自学习模糊逻辑控制器

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A robust self-learning fuzzy controller for a class of nonlinear MIMO systems is proposed. It is well known that the self-organizing fuzzy controller proposed by Procyk is sensitive to external signals such as set-point changes and/or disturbances. Such a phenomenon is observed in the fuzzy learning controllers that use a linear combination of error states for its adaptation law. To overcome such a difficulty a new learning scheme is introduced. The proposed learning scheme is implemented by constructing the performance decision table based on the principle of sliding mode control. Experimental results show that the proposed controller is robust to external signals.
机译:提出了一类非线性MIMO系统的强大自学习模糊控制器。众所周知,Procyk提出的自组织模糊控制器对外部信号敏感,例如设定点变化和/或干扰。在模糊学习控制器中观察到这种现象,用于使用误差状态的线性组合进行适应法。为了克服这种困难,介绍了一种新的学习方案。通过基于滑模控制原理构建性能决策表来实现所提出的学习方案。实验结果表明,所提出的控制器对外部信号稳健。

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