基于超稳定理论克服对象扰动自适应递归滤波辨识新算法  

A New Adaptive Recursive Filters Identification Algorithm of Overcoming the Disturbance Based on Hyperstable

作　　者：王向菊[1] 刘冬 吴士昌[3] 

机构地区：[1]河海大学计算机及信息工程学院,江苏常州213022 [2]煤炭科学总院常州自动化研究院,江苏常州213015 [3]燕山大学,河北秦皇岛066000

出　　处：《化工自动化及仪表》2009年第1期39-41,45,共4页Control and Instruments in Chemical Industry

摘　　要：结合超稳定理论与自适应逆控制理论,提出了一种新的能够克服对象扰动的自适应递归滤波辨识算法。由于该算法前向方块为1,已满足严格正实条件,省去了求解前向方块严格正实的计算;反向方块中用超稳定理论求出的参数迭代适应律,克服了用传输函数形式表示的递归滤波器采用梯度法时可能陷于局部极小的缺陷,解决了证明参数收敛问题,并且在模型与对象完全匹配时消除了系统扰动,辨识出的模型更精确实用。仿真结果证实了算法的可行性。On the basis of hyper-stable theory and adaptive inverse control theory, a new adaptive recursive filters identification algorithm which can overcome the disturbance was proposed. Since the forward square of the algorithm was 1 and had to meet strictly positive real conditions, the strictly positive real calculation of solving forward square was eliminated. The parameter iteration adaptation law solved by hyper-stable theory in backward square overcame the defects of possible local minimum caused by recursive filter with the form of transfer function adopting gradient meth- od. The proof of parameter convergence was solved. The system disturbance was eliminated when the model exact match the object and the identified model had more precise and practical. Simulation results show the feasibility of the new algorithm.

关 键 词：超稳定 递归滤波算法 补偿器 参数变化率 自适应逆 克服扰动 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]