摘要
在常规PID负荷协调控制回路中加入CMAC神经网络模型。利用神经网络的非线性映射能力,能很好地解决负荷协调控制对象的动态特性具有非线性、时变性、参数可变等问题。仿真对比试验表明:负荷协调控制系统引入CMAC逆模型后,系统的跟踪速度加快了大约1个周期,调节精度提高。CMAC逆模控制器有较好的适应性、鲁棒性。
Application of CMAC neural network inverse model in the coordinated control based on general PID is discussed. The coordinated control system has dynamic characteristic of nonlinear, varying parameter. Utilizing nonlinear mapping-capability of neural network solves these problems well. Simulation results show that CMAC has improved performance of original system. For example, response time reduces one cycle. When load varies, the inverse model controller also takes on good robust and adaptability. Figs 6, table 1 and refs 9.
出处
《动力工程》
CSCD
北大核心
2004年第1期83-86,共4页
Power Engineering
基金
国家重点基础发展规划(973)项目(G199902210516)
关键词
热能工程
控制优化
仿真
协调控制系统
CMAC逆模型
thermal engineering
control optimizing
simulation
coordinated control system
CMAC inverse model
