关于遗传算法模糊控制的研究

在控制对象的数学模型由于受非线性的时变的影响很难精确确定时，模糊控制是一个比较好的方法，但模糊控制规则易受人的因素的影响而归纳得不完善，并且不能自学习影响了模糊控制的效果。遗传算法可以搜索整个空间，不易陷入局部最优解，不受搜索空间的性假设的约束。可以解决非常困难的寻优问题，本文提出关于遗传算法的模糊控制，使控制规则得到优化，从而改善了控制性能。仿真实例表明这种方法是可行的。

Study of Fuzzy Control Based on Genetic Algorithms

Fuzzy control is a better control method when the detailed mathematical model of controlled object is very difficult to be achieved due to its nonlinearity and time variance. However sometimes fuzzy control rules can not be reduced well for lack of human experience, so that the result of fuzzy control is not satisfied. Very difficult function can be optimized by genetic algorithms because it can search whole space and it is not easy to jump into local optimization. Fuzzy control based on genetic algorithms is proposed in the paper.The control rules can be optimized and the control performance can be improved with this method. Simulation results show that it is feasible.