Robust Least Square Method and Its Application to Parameter Estimation
The system identification problem is researched when the input and output signal are both corrupted by noise. The robust least square (RLS) method and its application to parameter estimation problem, in which the perturbations are unknown but bounded (UBB), are introduced. The method can be interpreted as Tikhonov regularization procedure, with the advantage that it provides an exact bound on the robustness of solution and a rigorous way to compute the regularization parameter. Simulation results verify that the estimation precision and the robustness anti-noise of RLS are remarkably higher than other method when the input and output signal are both corrupted by noise.
Robust least square method (RLS) Parameter estimation Robustness
Zhang Mei Zhang Chenghui Zhang Huanshui Cui Peng Du Yanchun
School of Control Science and Engineering, Shandong University, Jinan 250010;School of Information a School of Control Science and Engineering, Shandong University, Jinan 250010
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）