In recent years, fuzzy systems have been proved to be universal function approximators, which means they can realize any nonlinear continuous control laws and dynamic models.

近年来，各类模糊系统已被证明是万能函数逼近器，它们能实现任意的非线性连续控制规律和动态模型。

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For a class of uncertain nonlinear systems, a combined adaptive fuzzy control method with the function of continuous supervisory control is proposed in this paper.

针对一类不确定非线性系统，本文提出了一种具有连续监督控制功能的组合型自适应模糊控制方法。

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For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.

针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。

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