摘要
利用BP神经网络的非线性映射能力对单元机组协调控制系统被控对象进行辨识,从而建立其动态模型;在这一模型的基础上对协调控制系统中的控制器参数优化进行研究,提出基于神经网络预测控制的协调控制策略。该方法很好地解决了协调控制系统中强耦合、非线性等问题。仿真实验表明该系统的跟踪速度加快、调节精度提高、并且具有较好的抗干扰性。
Utilizing the nonlinear mapping capability of BP neural networks, the pertaining object of control in the coordinated control system is being identified, and consequently its dynamic model established, on the basis of which optimization of the parameters of the controller in the coordinated control system is being studied and a coordinated control strategy based on predictive control with neural network proposed. In this way problems of profound coupling and nonlinearity, existing in coordinated control systems, can quite well be solved. Simulation tests indicate that such a system is featured by higher tracking speed, improved precision of adjustment and strengthened resistance capability against disturbances. Figs 6 and refs 7.
出处
《动力工程》
EI
CSCD
北大核心
2006年第3期392-395,共4页
Power Engineering
基金
电力行业青年促进费资助项目(SPQKJ015)
教育部回国人员科研启动经费项目(2004527)
关键词
自动控制技术
协调控制
神经网络
预测控制
automation technique
coordinated control
neural network
predictive control
作者简介
张建华（1969-）,女,山西忻州人,教授、博士.主要研究方向为：故障诊断与容错控制.
