基于线性网络的一类带扰动线性对象的逆控制研究  

Research on LNN-based Adaptive Inverse Control of a Class Linear Plant with Disturbance

作　　者：胡立坤[1] 王庆超[1] 

机构地区：[1]哈尔滨工业大学航天学院,哈尔滨市150001

出　　处：《微计算机信息》2006年第10S期33-36,共4页Control & Automation

基　　金：国家自然科学基金资助项目(60274002)

摘　　要：将线性网络应用于一类带扰动的线性对象,提出了一种基于该线性网络的自适应逆控制方案,该方案由辨识器、控制器和扰动消除器三部分构成,合理选择三个线性网络的输入,通过辨识器的在线学习,同时更新控制器和扰动消除器的权值,文章研究了该方案的收敛性和方案的跟踪性。根据可变步长权值收敛条件,设计了输入解相关变步长LMS算法调整辨识器权值方法。通过仿真研究了逆控制方法的有效性。The linear neural network is applied of a class linear plant with Disturbance, and a LNN-based adaptive inverse control scheme is presented. The control scheme is composed of three parts： identifier, controller and disturbance canceller. Three LLN＇s respectively selected inputs are so reasonable that when on-line training is only in the identifier, three networks＇ weight values are updated at the same time. The scheme＇s weight convergence is expatiated, and a desired reference can be tracked by the plant output. In according to the weight convergence condition of the variable step size least mean square algorithm, a new input-decorrelated variable step size least mean square algorithm is presented to make the scheme be applied in practice. A simulation examples are also presented to evaluate the scheme.

关 键 词：线性网络 LMS算法 自适应逆控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]