Parameter estimation for an input nonlinear state space system with time delay

Abstract This paper researches parameter estimation problems for an input nonlinear system with state time-delay. Combining the linear transformation and the property of the shift operator, the system is transformed into a bilinear parameter identification model. A gradient based and a least squares based iterative parameter estimation algorithms are presented for identifying the state time-delay system. The simulation results confirm that the proposed two algorithms are effective and the least squares based iterative algorithm has faster convergence rates than the gradient based iterative algorithm.

[1]  Simon X. Yang,et al.  Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace , 2013, IEEE Transactions on Cybernetics.

[2]  Jie Ding,et al.  Modified Subspace Identification for Periodically Non-uniformly Sampled Systems by Using the Lifting Technique , 2013, Circuits, Systems, and Signal Processing.

[3]  Feng Ding,et al.  State filtering and parameter estimation for state space systems with scarce measurements , 2014, Signal Process..

[4]  Er-Wei Bai,et al.  Iterative identification of Hammerstein systems , 2007, Autom..

[5]  Fei Liu,et al.  H∞ Filtering for Discrete-Time Systems With Stochastic Incomplete Measurement and Mixed Delays , 2012, IEEE Trans. Ind. Electron..

[6]  Pubudu N. Pathirana,et al.  Further result on reachable set bounding for linear uncertain polytopic systems with interval time-varying delays , 2011, Autom..

[7]  F. Ding,et al.  Least squares algorithm for an input nonlinear system with a dynamic subspace state space model , 2014 .

[8]  Bo Yu,et al.  Robust mixed H2/H∞ control of networked control systems with random time delays in both forward and backward communication links , 2011, Autom..

[9]  Feng Ding,et al.  States based iterative parameter estimation for a state space model with multi-state delays using decomposition , 2015, Signal Process..

[10]  Feng Ding,et al.  Parameter estimation for a multivariable state space system with d-step state-delay , 2013, J. Frankl. Inst..

[11]  Ligang Wu,et al.  Sliding mode control with bounded L2 gain performance of Markovian jump singular time-delay systems , 2012, Autom..

[12]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .

[13]  Jing Chen,et al.  Several gradient parameter estimation algorithms for dual-rate sampled systems , 2014, J. Frankl. Inst..

[14]  Feng Ding,et al.  Hierarchical estimation algorithms for multivariable systems using measurement information , 2014, Inf. Sci..

[15]  Feng Ding,et al.  State filtering and parameter estimation for linear systems with d-step state-delay , 2014, IET Signal Process..

[16]  Ligang Wu,et al.  Output Feedback Control of Markovian Jump Repeated Scalar Nonlinear Systems , 2014 .

[17]  D. Wang Brief paper: Lleast squares-based recursive and iterative estimation for output error moving average systems using data filtering , 2011 .

[18]  Feng Ding,et al.  Combined state and least squares parameter estimation algorithms for dynamic systems , 2014 .

[19]  Tao Tang,et al.  Recursive least squares estimation algorithm applied to a class of linear-in-parameters output error moving average systems , 2014, Appl. Math. Lett..

[20]  Jer-Nan Juang,et al.  Continuous-time bilinear system identification using single experiment with multiple pulses , 2012 .

[21]  Daqi Zhu,et al.  The bio-inspired model based hybrid sliding-mode tracking control for unmanned underwater vehicles , 2013, Eng. Appl. Artif. Intell..

[22]  Fei Liu,et al.  H∞ Control for Discrete-Time Markov Jump Systems With Uncertain Transition Probabilities , 2013, IEEE Transactions on Automatic Control.

[23]  Rik Pintelon,et al.  Blind maximum likelihood identification of Hammerstein systems , 2008, Autom..

[24]  Feng Ding,et al.  An efficient hierarchical identification method for general dual-rate sampled-data systems , 2014, Autom..

[25]  Fei Liu,et al.  Stabilization of Networked Control Systems With Random Delays , 2011, IEEE Transactions on Industrial Electronics.

[26]  T. Su,et al.  Delay-dependent stability analysis for recurrent neural networks with time-varying delay , 2008 .

[27]  Yong Zhang,et al.  Bias compensation methods for stochastic systems with colored noise , 2011 .

[28]  Vito Cerone,et al.  Parameter bounds for discrete-time Hammerstein models with bounded output errors , 2003, IEEE Trans. Autom. Control..

[29]  Feng Ding,et al.  Data filtering based recursive least squares algorithm for Hammerstein systems using the key-term separation principle , 2013, Inf. Sci..

[30]  Jie Ding,et al.  Auxiliary model based parameter estimation for dual-rate output error systems with colored noise ☆ , 2013 .

[31]  Ruifeng Ding,et al.  Parameter and State Estimation Algorithm for a State Space Model with a One-unit State Delay , 2013, Circuits Syst. Signal Process..

[32]  Baolin Liu,et al.  Recursive Extended Least Squares Parameter Estimation for Wiener Nonlinear Systems with Moving Average Noises , 2013, Circuits, Systems, and Signal Processing.

[33]  Feng Ding,et al.  Gradient based and least-squares based iterative identification methods for OE and OEMA systems , 2010, Digit. Signal Process..

[34]  Er-Wei Bai,et al.  Iterative identification of Hammerstein systems , 2007, Autom..

[35]  Er-Wei Bai An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems , 1998, Autom..

[36]  Tao Tang,et al.  Several gradient-based iterative estimation algorithms for a class of nonlinear systems using the filtering technique , 2014 .

[37]  Yong Zhang,et al.  Unbiased identification of a class of multi-input single-output systems with correlated disturbances using bias compensation methods , 2011, Math. Comput. Model..

[38]  Yuhua Chen,et al.  Indirect identification of continuous-time delay systems from step responses , 2011 .

[39]  Hu Yuanbiao Iterative and recursive least squares estimation algorithms for moving average systems , 2013 .

[40]  Dan Fan,et al.  Identification for disturbed MIMO Wiener systems , 2009 .

[41]  Junhong Li,et al.  Parameter estimation for Hammerstein CARARMA systems based on the Newton iteration , 2013, Appl. Math. Lett..