Floating-point coding is adopted to optimize fuzzy control rules, it can improve the efficiency and accuracy of calculation, also can guarantee fastness and global optimal.
采用浮点数编码对模糊控制规则进行优化，既提高了运算效率和计算精度，又保证了控制系统的快速性和全局最优性。
At last, the thesis suggests using the method of Genetic Algorithms to optimize the rules of fuzzy control.
最后，论文提出采用遗传算法对模糊控制规则进行优化设计。
At the same time, using the study and memory ability of neural networks, optimize subject function and control rules of control variables, which makes the control scheme more reasonable.
同时，应用神经网络的学习和记忆功能，对控制变量的隶属函数和控制规则进行优化，使控制方案更趋于合理。
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