Identification of nonlinear block-oriented systems with backlash and saturation
暂无分享,去创建一个
[1] Zhizhong Mao,et al. Adaptive control of Hammerstein–Wiener nonlinear systems , 2016, Int. J. Syst. Sci..
[2] Sakti Prasad Ghoshal,et al. Parametric Identification with Performance Assessment of Wiener Systems Using Brain Storm Optimization Algorithm , 2017, Circuits Syst. Signal Process..
[3] Yonghong Tan,et al. State estimation of a compound non-smooth sandwich system with backlash and dead zone , 2017 .
[4] Grzegorz Mzyk,et al. Instrumental variables for nonlinearity recovering in block-oriented systems driven by correlated signals , 2015, Int. J. Syst. Sci..
[5] Feng Ding,et al. Data filtering based forgetting factor stochastic gradient algorithm for Hammerstein systems with saturation and preload nonlinearities , 2016, J. Frankl. Inst..
[6] Wei Chen,et al. Hierarchical recursive least squares parameter estimation of non-uniformly sampled Hammerstein nonlinear systems based on Kalman filter , 2017, J. Frankl. Inst..
[7] T. Pan,et al. Identification of non-uniformly sampled Wiener systems with dead-zone non-linearities , 2017 .
[8] L. Dewan,et al. Instrument variable method based on nonlinear transformed instruments for Hammerstein system identification , 2018 .
[9] Vito Cerone,et al. Bounding the parameters of linear systems with input backlash , 2007, Proceedings of the 2005, American Control Conference, 2005..
[10] Feng Ding,et al. A filtering based multi-innovation gradient estimation algorithm and performance analysis for nonlinear dynamical systems , 2017 .
[11] Guangjun Liu,et al. Identification of Hammerstein systems using key-term separation principle, auxiliary model and improved particle swarm optimisation algorithm , 2013, IET Signal Process..
[12] G. Mzyk,et al. Direct identification of the linear block in Wiener system , 2016 .
[13] J. Vörös. Modelling and identification of nonlinear cascade systems with backlash input and static output nonlinearities , 2018, Mathematical and Computer Modelling of Dynamical Systems.
[14] Fouad Giri,et al. System identification of a class of Wiener systems with hysteretic nonlinearities , 2017 .
[15] F. Ding,et al. Decomposition-based least squares parameter estimation algorithm for input nonlinear systems using the key term separation technique , 2015 .
[16] Jozef Vörös,et al. Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearities , 2007, Syst. Control. Lett..
[17] Xiaoyu Huang,et al. Identification of Ground Vehicle Steering System Backlash , 2013 .
[18] Dakuo He,et al. Recursive parameter estimation for Hammerstein-Wiener systems using modified EKF algorithm. , 2017, ISA transactions.
[19] Jozef Vörös,et al. Modeling and identification of systems with backlash , 2010, Autom..
[20] Feng Ding,et al. Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering , 2017, J. Frankl. Inst..
[21] F. Ding,et al. Maximum likelihood Newton recursive and the Newton iterative estimation algorithms for Hammerstein CARAR systems , 2014 .
[22] Andrzej Janczak,et al. Instrumental variables approach to identification of a class of MIMO Wiener systems , 2007 .
[23] Minglang Yin,et al. Novel Wiener models with a time-delayed nonlinear block and their identification , 2016 .
[24] Shaoxue Jing,et al. Variable knot-based spline approximation recursive Bayesian algorithm for the identification of Wiener systems with process noise , 2017 .
[25] Feng Ding,et al. Filtering-Based Multistage Recursive Identification Algorithm for an Input Nonlinear Output-Error Autoregressive System by Using the Key Term Separation Technique , 2017, Circuits Syst. Signal Process..
[26] Jozef Vörös,et al. Iterative algorithm for parameter identification of Hammerstein systems with two-segment nonlinearities , 1999, IEEE Trans. Autom. Control..
[27] Feng Ding,et al. Hierarchical multi-innovation extended stochastic gradient algorithms for input nonlinear multivariable OEMA systems by the key-term separation principle , 2016 .
[28] Xuemei Ren,et al. Modified multi-innovation stochastic gradient algorithm for Wiener-Hammerstein systems with backlash , 2018, J. Frankl. Inst..
[29] Jozef Vörös,et al. Identification of nonlinear dynamic systems with input saturation and output backlash using three-block cascade models , 2014, J. Frankl. Inst..
[30] Jozef Vörös. Parametric Identification of Systems with General Backlash , 2012, Informatica.
[31] Yonghong Tan,et al. On-line identification algorithm and convergence analysis for sandwich systems with backlash , 2011 .
[32] Feng Ding,et al. Combined state and multi-innovation parameter estimation for an input non-linear state-space system using the key term separation , 2016 .
[33] Fouad Giri,et al. Identification of Hammerstein systems in presence of hysteresis-backlash and hysteresis-relay nonlinearities , 2008, Autom..
[34] Er-Wei Bai,et al. Generalized Wiener system identification: General backlash nonlinearity and finite impulse response linear part , 2014 .
[35] Lennart Ljung,et al. Theory and Practice of Recursive Identification , 1983 .
[36] M. Chidambaram,et al. Computer Control of Processes , 2001 .
[37] C. L. Philip Chen,et al. Adaptive inverse compensation for actuator backlash with piecewise time-varying parameters , 2018, Int. J. Control.
[38] Yan Wang,et al. A Multi-innovation Recursive Least Squares Algorithm with a Forgetting Factor for Hammerstein CAR Systems with Backlash , 2016, Circuits Syst. Signal Process..
[39] J. Voros. AN ITERATIVE METHOD FOR HAMMERSTEIN-WIENER SYSTEMS PARAMETER IDENTIFICATION , 2004 .
[40] Brett Ninness,et al. Generalised Hammerstein–Wiener system estimation and a benchmark application , 2012 .
[41] Fouad Giri,et al. Combined frequency-prediction error identification approach for Wiener systems with backlash and backlash-inverse operators , 2014, Autom..
[42] Xuemei Ren,et al. Decomposition-based recursive least-squares parameter estimation algorithm for Wiener-Hammerstein systems with dead-zone nonlinearity , 2017, Int. J. Syst. Sci..
[43] Kazys Kazlauskas,et al. On Intelligent Extraction of an Internal Signal in a Wiener System Consisting of a Linear Block Followed by Hard-Nonlinearity , 2013, Informatica.
[44] Zygmunt Hasiewicz,et al. On Nonparametric Identification of Wiener Systems , 2007, IEEE Transactions on Signal Processing.
[45] Hugues Garnier,et al. Refined instrumental variable method for Hammerstein-Wiener continuous-time model identification , 2013 .
[46] Feng Ding,et al. The recursive least squares identification algorithm for a class of Wiener nonlinear systems , 2016, J. Frankl. Inst..
[47] F. Ding,et al. Newton iterative identification method for an input nonlinear finite impulse response system with moving average noise using the key variables separation technique , 2014, Nonlinear Dynamics.
[48] Er-Wei Bai,et al. A blind approach to the Hammerstein-Wiener model identification , 2002, Autom..
[49] Jozef Vörös. Modeling and Identification of Nonlinear Cascade and Sandwich Systems with General Backlash , 2014 .
[50] Ruifeng Ding,et al. Gradient-based iterative algorithm for Wiener systems with saturation and dead-zone nonlinearities , 2014 .