基于辅助变量的压缩采样匹配追踪闭环系统辨识方法

An instrumental variable based compressed sampling matching pursuit method for closed-loop identification

针对被控对象和反馈通道均具有未知时滞的闭环系统,提出一种基于辅助变量的压缩采样匹配追踪辨识方法.该方法利用辅助变量方法对压缩采样匹配追踪算法进行改进,获得过参数化辨识模型稀疏参数向量的估计,根据稀疏向量的结构得到前向通道的参数估计和时滞估计,进而根据模型等价原理获得反馈通道的参数估计.仿真结果表明,所提出方法仅需少量的迭代即可获得这类闭环系统参数与时滞的有效估计.

For the identification of a class of closed-loop systems with unknown time-delays in both the control plant and the feedback controller, an instrumental variable based compressed sampling matching pursuit method is developed.By using the instrumental variable identification idea to modify the compressed sampling matching pursuit algorithm,the sparse parameter vector of the overparameterized identification model is firstly estimated. Then the estimates of the control plant parameters and the time-delays can be extracted from the estimated parameter vector, and the parameters of the feedback controller can be obtained by using the model equivalence principle. Simulation results show that the proposed method can effectively estimate the parameters and time-delays for the class of closed-loop systems with only a few iterations.