An extended AUDI algorithm for simultaneous identification of forward and backward paths in closed-loop systems

Abstract In closed-loop system identification, most of the existing methods only focus on the forward path, yet few on simultaneous identification of the forward and backward paths. Meanwhile, an augmented UD identification (AUDI) algorithm has been proved effective in open-loop system identification, but it only extracts the forward path information, while not including the backward path information provided in an augmented information matrix, which is helpful for the closed-loop system identification. In this paper, an extended AUDI (EAUDI) is proposed to simultaneously identify the model orders and parameters of both forward and backward paths of a closed-loop system. The conditions of identifiability and uniform convergence for closed-loop systems using the EAUDI algorithm are also given. The effectiveness of this algorithm is demonstrated by a numerical example.

[1]  Jyh-Cheng Jeng,et al.  Closed-Loop Identification of Dynamic Models for Multivariable Systems with Applications to Monitoring and Redesign of Controllers , 2011 .

[2]  Graham C. Goodwin,et al.  Finite sample properties of indirect nonparametric closed-loop identification , 2002, IEEE Trans. Autom. Control..

[3]  Sachin C. Patwardhan,et al.  Closed-loop identification using direct approach and high order ARX/GOBF-ARX models , 2011 .

[4]  Lemma Dendena Tufa,et al.  Closed-loop identification of systems with uncertain time delays using ARX–OBF structure , 2011 .

[5]  Lennart Ljung,et al.  A Tutorial On Multiple Model Least-Squares and Augmented UD Identification , 1995 .

[6]  Marion Gilson,et al.  Instrumental variable methods for closed-loop system identification , 2005, Autom..

[7]  D. Grant Fisher,et al.  MIMO System Identification using Augmented UD Factorization , 1991, 1991 American Control Conference.

[8]  T. Söderström,et al.  Instrumental Variable Methods for Closed Loop Systems , 1987 .

[9]  D. Grant Fisher,et al.  A recursive algorithm for simultaneous identification of model order and parameters , 1990, IEEE Trans. Acoust. Speech Signal Process..

[10]  Charles Q. Zhan,et al.  A practical global multi-stage method for fully automated closed-loop identification of industrial processes , 2007 .

[11]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[12]  Jan Dimon Bendtsen,et al.  Closed-loop system identification with new sensors , 2008, 2008 47th IEEE Conference on Decision and Control.

[13]  Jin Wang,et al.  Closed-loop subspace identification using the parity space , 2006, Autom..