摘要
提出了一种新颖的直接自适应模糊控制方法。基于简化了的 T-S(Takagi-Sugeno)模糊推理规则 ,采用神经网络权值的联想式学习修正方法 ,对 T-S模糊推理规则进行在线修正 ,给出了相应的神经网络实现结构 ,从而实现了不需要建立受控对象模型的直接自适应模糊控制。对一混流式水轮机组的仿真控制实验结果证明了所提出方法具有设计简单、鲁棒性强的优点 ,能适应水轮机组在不同工况下的控制要求。图 9参
To hydraulic turbine generator with complex dynamic characteristics and uncertainties, a novel direct adaptive fuzzy control approach is proposed in this paper. Based on the simplified Takagi Sugeno fuzzy inference rule and the associative learning strategy of neural network for tuning connect weights, an equivalent fuzzy neural network is given. The controller with this fuzzy neural network can realize the adaptive fuzzy control without modeling the plant. A series simulation test for a hydraulic turbine generator show that the presented control method not only has simple design procedure and strong robustness, but also achieves good performances of the hydraulic turbine generator. Figs 9 and refs 4.
出处
《动力工程》
CSCD
北大核心
2001年第2期1180-1184,共5页
Power Engineering
关键词
水轮发电机组
模糊控制
联想式学习
模糊神经网络
非模型控制
自适应控制
hydraulic turbine generators
adaptive fuzzy control, associative learning strategy
fuzzy neural network
model free control