基于遗传算法的自适应神经模糊控制器

Self-adaptive Neural Fuzzy System Controller Based on Genetic Algorithm

分析了自适应神经模糊系统的特性,以此设计一个智能控制器,控制器的输入为误差和误差变化率,输出为控制量。遗传算法是一种有效的全局最优搜索算法,对于复杂、非线性的空间也能够快速地搜索最优解,因而本文利用遗传算法来优化自适应神经模糊控制器的参数。仿真实验表明,该方法优化得到的控制器具有优良的控制效果。

The paper analyzes the characteristic of selfadaptive neural fuzzy system, and designs an intelligent controller. The input of controller are error and rate of error, the output is control values. Genetic Algorithm (GA) is a kind of useful global searching algorithm even for complex, nonlinear systems.In this paper, we apply GA for the optimization of parameters. Simulation results show the good performance of this controller.