基于改进型神经动态规划算法的单容液位优化控制  

Optimal Control Based on Improved Neural Dynamic Programming Algorithm for Single-tank Liquid Level

作　　者：王琦[1] 王淼[1] 孙晨[2] 

机构地区：[1]国电南瑞科技股份有限公司,南京210000 [2]新乡职业技术学院,新乡453000

出　　处：《科学技术与工程》2012年第28期7411-7415,共5页Science Technology and Engineering

摘　　要：单容液位控制系统是一个强非线性、多约束、时滞的复杂系统,传统的PID控制算法很难对其进行精确自适应优化控制。介绍了一种改进型的神经动态规划(NDP)算法,其中模型网络用小波神经网络来替代,并针对单容液位控制系统的液位进行自适应优化控制。仿真结果表明,基于神经网络的NDP算法在鲁棒性、控制精度和控制效果都优于传统的PID算法。Single-tank liquid level system is a complex system which is nonlinear, multi-constraint, and delays. It is difficult of traditional PID control algorithm to adaptively adopt optimal control on single-tank liquid level system. An improved neural dynamic programming （NDP） algorithm which the model network is wavelet neural network is introduced to solve the problem adaptively adopt optimal control on liquid level of single-tank liquid level system. The results show that NDP algorithm has the better robustness, control accuracy and control effects than traditional PID control algorithm.

关 键 词：神经网络 神经动态规划(NDP) 单容液位控制 神经网络控制 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]