Joint Parameter and Time-Delay Identification Algorithm and Its Convergence Analysis for Wiener Time-Delay Systems

New developments for parameter and time-delay identification are presented for discrete nonlinear systems with delayed input. The proposed approach is based on overparametrization approach which involves subsuming the delay term into an extended numerator polynomial of the linear block of Wiener time-delay system. On this basis, the parameter identification problem can be then solved using recursive least squares-based optimization techniques and then, the delay is calculated directly based on the extended numerator polynomial identified: For a noise-free system, all extended numerator parameters are equal to zero. However in the noisy-output case, it is necessary to introduce an upper bound and the extended parameters whose values are smaller than a threshold level should be identified as zero. Then, the delay is determined as the first number of null extended parameter values. In addition, the convergence of the identified parameter vector is studied. The performances of the proposed identification algorithms are illustrated through simulation examples.

[1]  Jacob Benesty,et al.  Recursive Least-Squares Algorithms for the Identification of Low-Rank Systems , 2019, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[2]  Asma Atitallah,et al.  System identification: Parameter and time-delay estimation for Wiener nonlinear systems with delayed input , 2018, Trans. Inst. Meas. Control.

[3]  Jie Su,et al.  Time-delay estimation for SISO systems using SWσ. , 2018, ISA transactions.

[4]  J. Timmer,et al.  Estimation of Delay Times in Biological Systems , 2003, Annals of Biomedical Engineering.

[5]  E. Bai,et al.  Block Oriented Nonlinear System Identification , 2010 .

[6]  Johan A. K. Suykens,et al.  A two-experiment approach to Wiener system identification , 2018, Autom..

[7]  Ling Yu,et al.  A Time Delay Estimation Algorithm Based on the Weighted Correntropy Spectral Density , 2017, Circuits Syst. Signal Process..

[8]  Federico Milano,et al.  Small-Signal Stability Analysis for Non-Index 1 Hessenberg Form Systems of Delay Differential-Algebraic Equations , 2016, IEEE Transactions on Circuits and Systems I: Regular Papers.

[9]  Asma Atitallah,et al.  An Optimal Two Stage Identification Algorithm for Discrete Hammerstein Time Delay Systems , 2016 .

[10]  Feng Ding,et al.  Two-Stage Generalized Projection Identification Algorithms for Stochastic Systems , 2019, Circuits Syst. Signal Process..

[11]  Jean-Pierre Richard,et al.  Time-delay systems: an overview of some recent advances and open problems , 2003, Autom..

[12]  Feng Ding,et al.  The recursive least squares identification algorithm for a class of Wiener nonlinear systems , 2016, J. Frankl. Inst..

[13]  Hisyam Anwaruddin,et al.  A new approach to the identification of distillation column based on hammerstein model , 2014 .

[14]  Qiang Chen,et al.  Conversion of SISO processes with multiple time-delays to single time-delay processes , 2017 .

[15]  S. Billings Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains , 2013 .

[16]  Sakti Prasad Ghoshal,et al.  Parametric Identification with Performance Assessment of Wiener Systems Using Brain Storm Optimization Algorithm , 2017, Circuits Syst. Signal Process..

[17]  Kamel Abderrahim,et al.  Identification of Wiener Time Delay Systems Based on Hierarchical Gradient Approach , 2015 .

[18]  Wei Xing Zheng,et al.  A Recursive Identification Algorithm for Wiener Nonlinear Systems with Linear State-Space Subsystem , 2018, Circuits Syst. Signal Process..

[19]  José A. Romagnoli,et al.  Application of Wiener model predictive control (WMPC) to a pH neutralization experiment , 1999, IEEE Trans. Control. Syst. Technol..

[20]  Weicong Na,et al.  A Wiener-Type Dynamic Neural Network Approach to the Modeling of Nonlinear Microwave Devices , 2017, IEEE Transactions on Microwave Theory and Techniques.

[21]  M. J. Korenberg,et al.  The identification of nonlinear biological systems: Wiener and Hammerstein cascade models , 1986, Biological Cybernetics.

[22]  Federico Milano,et al.  On the Stability Analysis of Systems of Neutral Delay Differential Equations , 2018, Circuits, Systems, and Signal Processing.

[23]  Roberto Kawakami Harrop Galvão,et al.  Wiener-System Subspace Identification for Mobile Wireless mm-Wave Networks , 2007, IEEE Transactions on Vehicular Technology.

[24]  Kamel Abderrahim,et al.  New results on wiener time delay system identification , 2016, 2016 European Control Conference (ECC).

[25]  E. D. Klerk,et al.  Aspects of semidefinite programming : interior point algorithms and selected applications , 2002 .

[26]  Ioannis K. Dassios,et al.  Optimal Solutions for Non-consistent Singular Linear Systems of Fractional Nabla Difference Equations , 2014, Circuits, Systems, and Signal Processing.

[27]  Yu Qian,et al.  Dynamic flexibility analysis of chemical reaction systems with time delay: Using a modified finite element collocation method , 2011 .

[28]  C. Reutenauer,et al.  A formula for the determinant of a sum of matrices , 1987 .

[29]  Xiangli Li,et al.  Least-Squares-Based Iterative Identification Algorithm for Wiener Nonlinear Systems , 2013, J. Appl. Math..

[30]  Kai Xu,et al.  Three-Dimensional Modeling of Spatial Reinforcement of Soil Nails in a Field Slope under Surcharge Loads , 2013, J. Appl. Math..

[31]  S. Niculescu Delay Effects on Stability: A Robust Control Approach , 2001 .

[32]  Kamel Abderrahim,et al.  On convergence analysis of an identification algorithm for Hammerstein-Wiener systems with unknown time-delay , 2017 .

[33]  D. Harville Matrix Algebra From a Statistician's Perspective , 1998 .

[34]  Koen Tiels,et al.  Identification of block-oriented nonlinear systems starting from linear approximations: A survey , 2016, Autom..

[35]  O. Nelles Nonlinear System Identification , 2001 .

[36]  Aidan O'Dwyer Time delay estimation in signal processing applications: an overview , 2002 .

[37]  O. Nelles Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models , 2000 .

[38]  Robin De Keyser,et al.  Nonlinear Predictive Control of processes with variable time delay. A temperature control case study , 2008, 2008 IEEE International Conference on Control Applications.

[39]  Le Yi Wang,et al.  Identification of Wiener systems with quantized inputs and binary-valued output observations , 2017, Autom..

[40]  Jeen-Shing Wang,et al.  A Wiener-type recurrent neural network and its control strategy for nonlinear dynamic applications , 2009 .

[41]  Andy Srinivasan,et al.  Wiener Model Based Real-Time Identification and Control of Heat Exchanger Process , 2008 .