Identification Algorithm Based on the Approximate Least Absolute Deviation Criteria

作     者：Bao-Chang Xu Xin-Le Liu Department of Automation, China University of Petroleum, Beijing 102249, China 

作者机构：Department of Automation China University of Petroleum Beijing China 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2012年第9卷第5期

页      面：501-505页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 0802[工学-机械工程] 081101[工学-控制理论与控制工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：supported by Important National Science & Technology Specific Projects (No.2011ZX05021-003) 

主　　题：System identification least absolute deviation (LAD) Gauss-Newton algorithm robustness disorder and peak noise 

摘      要：Considering the situation that the least-squares (LS) method for system identification has poor robustness and the least absolute deviation (LAD) algorithm is hard to construct, an approximate least absolute deviation (ALAD) algorithm is proposed in this paper. The objective function of ALAD is constructed by introducing a deterministic function to approximate the absolute value function. Based on the function, the recursive equations for parameter identification are derived using Gauss-Newton iterative algorithm without any simplification. This algorithm has advantages of simple calculation and easy implementation, and it has second order convergence speed. Compared with the LS method, the new algorithm has better robustness when disorder and peak noises exist in the measured data. Simulation results show the efficiency of the proposed method.