摘要
水轮机调节系统的被控对象是一个时变、非线性和含非最小相位环节的复杂系统,为了寻求一种好的控制算法来提高控制系统性能,提出了3种改进后的模糊神经控制,即比例积分智能权函数模糊控制、定增益单神经元PSD控制和定增益单神经元智能权函数神经模糊复合控制。仿真分析表明:比例积分智能权函数模糊控制和定增益单神经元PSD控制既有较快的响应速度,又能实现无差调节特性;定增益单神经元智能权函数神经模糊复合控制既有快速的响应速度,又有良好的稳态特性和动态特性,同时鲁棒性好。它们均优于常规PID控制。
As hydro-turbine governing system is time-variant and non-linear and non-minimum phase, it is necessary to find a better algorithm to improve the ability of control system. This paper proposes three improved ways; PI intelligent weight function fuzzy control (PIIWFFC) , fixed-gain single neuron PSD control (FGSNC) and compound neural fuzzy control (NFC). PIIWFFC and FGSNC have quick response and no steady error. NFC has not only quick response, good static and dynamic performances, but also good robustness. Simulation and analysis show that they are effective and better than routine PID control.
出处
《长江科学院院报》
CSCD
北大核心
2003年第2期45-49,共5页
Journal of Changjiang River Scientific Research Institute
基金
国家九五重大科技攻关资助项目(97-312-01-20)
关键词
水轮机调节系统
权函数
模糊控制
神经控制
hydro-turbine governing system
weight function
fuzzy control
neural control
