Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Recursive subspace identification of linear and non-linear Wiener state-space models
Automatica (Journal of IFAC)
N4SID and MOESP algorithms to highlight the ill-conditioning into subspace identification
International Journal of Automation and Computing
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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.