受控系统模糊控制器的BP网络模型构建与仿真

BP Neural Network Model Construction and Simulation for Fuzzy Controller of the Controlled System

通过对受控系统的仿真分析,设计模糊控制器,实现受控系统的模糊控制,进而达到受控系统的控制性能指标。而模糊控制器的思想与方法在微型计算机中的实现难度很大,其涉及的计算不容易实现[1],考虑BP网络模型是确定的函数模型,BP网络模型很容易通过编程实现。因此利用BP网络在线学习求取模糊控制器的函数模型,从而实现基于微型计算机的模糊控制技术,通过仿真BP网络模型其控制效果与模糊控制器控制效果吻合。

Through the controlled system simulation analysis, fuzzy controller is designed to realize fuzzy control of the controlled system, thus achieving the controlled system control performance. The ideas and methods of fuzzy controller in microcomputer implementation is very difficult, and the calculation is not easy to achieve. But the BP neural network model is the certain function model, BP network model is easily achieved by programming. Therefore, BP network online learning is used to strike a function model of fuzzy controller, in order to achieve fuzzy control technology of the system based on microcomputer. Through simulation, BP network model and fuzzy controller control effects consistent results.