文献类型：期刊文献

中文题名：基于模糊神经网络的通用模型自适应控制

英文题名：Common model adaptive control based on fuzzy neural network

作者：樊四良[1];常亮[1];郭丙君[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2009

期号：5

起止页码：9

中文期刊名：自动化与仪器仪表

外文期刊名：Automation & Instrumentation

收录：CSTPCD

语种：中文

中文关键词：通用模型控制;模糊神经网络;自适应控制

外文关键词：Common model control ; Fuzzy neural network ; Adaptive control

摘要：自适应控制是一种提高系统鲁棒性的有效方法。模糊神经网络具有了模糊逻辑和神经网络两者的优点,结合模糊神经网络(Fuzzy Neural Network-FNN)自适应控制策略和通用模型控制(Common Model Control-CMC)方法,以此来实现被控对象的逆控制,提出了基于模糊神经网络的通用模型自适应控制(FNNC-CMAC)。此控制方法参考轨迹是一条典型二阶曲线,仿真结果验证了鲁棒性,与基于模糊神经网络的通用模型控制及基于模糊逻辑的通用模型自适应控制相比,其控制性能更好。
Adaptive control is one of effective methods to improve robustness of the control system FNN has the advantages both of fuzzy logic and neural network. Combine FNN adaptive control scheme with CMC method to realize the inverted control so the chapter presents FNNC-CMAC. The reference trajectory is a classic second order curve in the above control method. The simulation results validate the robustness of the common model adaptive control based on FNN, which the resuUt is better than common model control based on FNN and common model adaptive, ptive control based on fuzzy logic.