This paper proposes a design of the self adaptive learning fuzzy controller based on Genetic Algorithms optimization.

本文提出一种基于基因算法优化的自学习模糊控制器的设计。

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Considering fuzzy C-means clustering algorithms are sensitive to initialization and easy fall - en to local minimum, a novel optimization method is proposed.

针对模糊C均值聚类算法对初始值敏感、易陷入局部最优的缺陷，提出一种新的优化方法。

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In addition, the paper makes use of Genetic Algorithms to optimize learning rates and inertia coefficients of Fuzzy-neural network, which can ensure that the controller achieves optimization control.

此外，通过遗传算法对模糊神经网络的学习速率和惯性系数等进行了优化，为控制系统实现最优控制提供了有力保证。

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