基于最优预测的神经元模糊自整定PID控制  

Adaptive Neuron-fuzzy PID Controller Based on Optimal Prediction

作　　者：李健[1] 段军霞[1] 何小阳[1] 

机构地区：[1]广西大学电气工程学院,广西南宁530004

出　　处：《控制工程》2007年第6期586-588,共3页Control Engineering of China

摘　　要：针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性,提出了一种基于最优预测的神经元模糊自整定PID控制算法。该算法利用最优预测克服时滞,利用神经元学习功能和模糊控制调节神经元增益克服系统的非线性和时变问题。仿真结果表明,该控制算法鲁棒性强、响应速度快,具有工业控制应用价值。To the widely existed characteristics of time-delay, non-linear and time-varying of parameters in the industry process, an adaptive neuron-fuzzy PID controller based on optimal prediction is presented, The time-delay is overcome by Optimal prediction, Problems of the nonlinearity and time-varying are solved by leaning-function of neuron and fuzzy controller adjusting gain. The simulation results show the high response speed and robustness of the proposed algorithm and the practical value in industry control.

关 键 词：最优预测 神经元 模糊 时滞 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]