基于自适应遗传算法的模糊控制器优化设计

Optimal Design of Fuzzy Logic Controller Based on Adaptive Genetic Algorithm

改变传统的优化模糊控制器的方法,采用自适应遗传算法优化设计了一种控制效果较好的模糊控制器。在遗传算法改进方面,不以传统的定值常量作为交叉和变异概率,而是根据遗传算法本身计算出来的个体适应度来自适应的调节交叉和变异概率的大小,以克服采用定值常量作为交叉和变异概率所带来的早熟现象和效率相对较低的问题。仿真结果表明,改进的模糊控制器具有更好的控制效果。

This paper abolishes traditional methods and designs a new type of fuzzy logic controller which based on adaptive genetic algorithm.In order to improve genetic algorithm ,this paper abolishes the constant ,uses the function of fitness degree which from the genetic algorithm itself as the crossover and mutation ratio, so the ratio can change with the fitness degree and adapt to the fuzzy logic controller, and it can avoid the limitation of the tra- ditional genetic algorithm.According to simulation results, this improved fuzzy logic controller has a better control result.