采用神经网络优化调整因子的模糊温度控制器

The Fuzzy Temperature Controller with Tuning Factors Are Optimized by Neural Network

含多个调整因子的模糊控制器的调整因子的确定是一个参数为避兔参数选择上的盲目性,本文采用BP神经网终对系统的调整因子进行了寻优,仿真及实际后的模糊控制器在对加热炉的温度实施控制时,性能得到很大改善,这说明利用神经网络对调整因子进行优化的方法有较高的应用价值。

To find best tuning factors of the fuzzy temperature controller with multi-tuning factors is a. problem of optimizing combined parameters. A BP-neural network is introduced in this paper to optimize the tuning factors of the system to avoid selecting parameters blindly. The temperature of a heating furnace is controlled by the fuzzy controller and the result of simulation and practical running indicate that the performance be greatly improved after the tuning factors have been optimized by neural network. It also shows that the method has great value in application.