Parameter estimation algorithm for multivariable controlled autoregressive autoregressive moving average systems

Abstract This paper investigates parameter estimation problems for multivariable controlled autoregressive autoregressive moving average (M-CARARMA) systems. In order to improve the performance of the standard multivariable generalized extended stochastic gradient (M-GESG) algorithm, we derive a partially coupled generalized extended stochastic gradient algorithm by using the auxiliary model. In particular, we divide the identification model into several subsystems based on the hierarchical identification principle and estimate the parameters using the coupled relationship between these subsystems. The simulation results show that the new algorithm can give more accurate parameter estimates of the M-CARARMA system than the M-GESG algorithm.

[1]  Jianqiang Pan,et al.  A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems , 2017 .

[2]  Min Liu,et al.  Research on a handwritten character recognition algorithm based on an extended nonlinear kernel residual network , 2018, KSII Trans. Internet Inf. Syst..

[3]  Steven X. Ding,et al.  Unbiased Minimum Variance Fault and State Estimation for Linear Discrete Time-Varying Two-Dimensional Systems , 2017, IEEE Transactions on Automatic Control.

[4]  Feng Ding,et al.  A hierarchical least squares identification algorithm for Hammerstein nonlinear systems using the key term separation , 2018, J. Frankl. Inst..

[5]  Long Chen,et al.  On Some Separated Algorithms for Separable Nonlinear Least Squares Problems , 2018, IEEE Transactions on Cybernetics.

[6]  Feng Liu,et al.  Regularity of discrete multisublinear fractional maximal functions , 2017 .

[7]  Ying Shen,et al.  Exit problems for jump processes with applications to dividend problems , 2013, J. Comput. Appl. Math..

[8]  Weihai Zhang,et al.  ℋ- index for discrete-time stochastic systems with Markovian jump and multiplicative noise , 2018, Autom..

[9]  Jian Pan,et al.  Adaptive Gradient-Based Iterative Algorithm for Multivariable Controlled Autoregressive Moving Average Systems Using the Data Filtering Technique , 2018, Complex..

[10]  Yinghong Wen,et al.  Performance Evaluation with Improved Receiver Design for Asynchronous Coordinated Multipoint Transmissions , 2016 .

[11]  Peng Li,et al.  Parallel processing algorithm for railway signal fault diagnosis data based on cloud computing , 2018, Future Gener. Comput. Syst..

[12]  C. Yin,et al.  The Perturbed Compound Poisson Risk Process with Investment and Debit Interest , 2010 .

[13]  Ruifeng Ding,et al.  Two-stage least squares based iterative identification algorithm for controlled autoregressive moving average (CARMA) systems , 2012, Comput. Math. Appl..

[14]  C. Yin,et al.  Optimal dividends problem with a terminal value for spectrally positive Levy processes , 2013, 1302.6011.

[15]  Feng Ding,et al.  Iterative Parameter Estimation for Signal Models Based on Measured Data , 2018, Circuits Syst. Signal Process..

[16]  F. Ding.  Coupled-least-squares identification for multivariable systems , 2013 .

[17]  Feng Ding,et al.  Combined state and parameter estimation for a bilinear state space system with moving average noise , 2018, J. Frankl. Inst..

[18]  Ling Xu.  The parameter estimation algorithms based on the dynamical response measurement data , 2017 .

[19]  José Francisco Gómez-Aguilar,et al.  Parameter identification of periodical signals: Application to measurement and analysis of ocean wave forces , 2017, Digit. Signal Process..

[20]  Ao Li,et al.  A low-complexity Lanczos-algorithm-based detector with soft-output for multiuser massive MIMO systems , 2017, Digit. Signal Process..

[21]  Shuang Wu,et al.  Efficient parameter estimation method for maneuvering targets in discrete randomly-modulated radar , 2017, Digit. Signal Process..

[22]  Feng Ding,et al.  A recursive least squares parameter estimation algorithm for output nonlinear autoregressive systems using the input-output data filtering , 2017, J. Frankl. Inst..

[23]  Erfu Yang,et al.  State filtering‐based least squares parameter estimation for bilinear systems using the hierarchical identification principle , 2018, IET Control Theory & Applications.

[24]  Yu Guo,et al.  Robust adaptive estimation of nonlinear system with time‐varying parameters , 2015 .

[25]  Fuad E. Alsaadi,et al.  Iterative parameter identification for pseudo-linear systems with ARMA noise using the filtering technique , 2018 .

[26]  Daqi Zhu,et al.  An Adaptive SOM Neural Network Method for Distributed Formation Control of a Group of AUVs , 2018, IEEE Transactions on Industrial Electronics.

[27]  Dongqing Wang,et al.  Recursive maximum likelihood identification method for a multivariable controlled autoregressive moving average system , 2016, IMA J. Math. Control. Inf..

[28]  Liang Liang,et al.  Optimization of Information Interaction Protocols in Cooperative Vehicle-Infrastructure Systems , 2018 .

[29]  Jing Na,et al.  Improving transient performance of adaptive control via a modified reference model and novel adaptation , 2017 .

[30]  Feng Ding,et al.  A multi-innovation state and parameter estimation algorithm for a state space system with d-step state-delay , 2017, Signal Process..

[31]  Hong Wang,et al.  Fault Diagnosis and Tolerant Control for Discrete Stochastic Distribution Collaborative Control Systems , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[32]  Xia Zhang,et al.  Standard Analysis for Transfer Delay in CTCS-3 , 2017 .

[33]  Donghua Zhou,et al.  Control Performance Assessment for ILC-Controlled Batch Processes in a 2-D System Framework , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[34]  Jiling Ding,et al.  Recursive and Iterative Least Squares Parameter Estimation Algorithms for Multiple-Input–Output-Error Systems with Autoregressive Noise , 2018, Circuits Syst. Signal Process..

[35]  Feng Ding,et al.  Iterative identification algorithms for bilinear-in-parameter systems with autoregressive moving average noise , 2017, J. Frankl. Inst..

[36]  Weihai Zhang,et al.  Global stabilization for a class of stochastic nonlinear systems with SISS‐like conditions and time delay , 2018 .

[37]  Feng Ding,et al.  Parameter estimation for control systems based on impulse responses , 2017 .

[38]  Yuquan Chen,et al.  Identification for Hammerstein nonlinear ARMAX systems based on multi-innovation fractional order stochastic gradient , 2018, Signal Process..

[39]  Jiling Ding,et al.  The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise , 2017, Complex..

[40]  Feng Ding,et al.  A filtering based multi-innovation gradient estimation algorithm and performance analysis for nonlinear dynamical systems , 2017 .

[41]  C. Yin,et al.  Optimality of the threshold dividend strategy for the compound Poisson model , 2011 .

[42]  F. Alsaadi,et al.  Recursive parameter identification of the dynamical models for bilinear state space systems , 2017 .

[43]  T. Hayat,et al.  Hierarchical Parameter Estimation for the Frequency Response Based on the Dynamical Window Data , 2018, International Journal of Control, Automation and Systems.

[44]  Feng Liu,et al.  On the regularity of maximal operators supported by submanifolds , 2017 .

[45]  Wen-Qin Wang,et al.  Sparsity-aware transmit beamspace design for FDA-MIMO radar , 2018, Signal Process..

[46]  Yong Xiang,et al.  Blind channel estimation and signal retrieving for MIMO relay systems , 2016, Digit. Signal Process..

[47]  Min Gan,et al.  A Variable Projection Approach for Efficient Estimation of RBF-ARX Model , 2015, IEEE Transactions on Cybernetics.

[48]  Feng Ding,et al.  Some new results of designing an IIR filter with colored noise for signal processing , 2018, Digit. Signal Process..

[49]  Feng Ding,et al.  Hierarchical least-squares based iterative identification for multivariable systems with moving average noises , 2010, Math. Comput. Model..

[50]  Yu Guo,et al.  Robust adaptive parameter estimation of sinusoidal signals , 2015, Autom..

[51]  Feng Ding,et al.  Decomposition-based recursive least squares identification methods for multivariate pseudo-linear systems using the multi-innovation , 2018, Int. J. Syst. Sci..

[52]  Wei Wang,et al.  Maximum likelihood least squares identification for systems with autoregressive moving average noise , 2012 .

[53]  Rui Liu,et al.  Contract design for relay incentive mechanism under dual asymmetric information in cooperative networks , 2018, Wirel. Networks.

[54]  Feng Liu,et al.  Singular integrals related to homogeneous mappings in Triebel-Lizorkin spaces , 2017 .

[55]  Feng Ding,et al.  Least Squares based Iterative Parameter Estimation Algorithm for Stochastic Dynamical Systems with ARMA Noise Using the Model Equivalence , 2018 .