Gradient-based iterative algorithm for Wiener systems with saturation and dead-zone nonlinearities

JVC/Journal of Vibration and Control

Volumn 20, Issue 4, 2014, Pages 634-640

  Chen, Jing ^a,b   Lu, Xianling ^a   Ding, Ruifeng ^a  

^a JIANGNAN UNIVERSITY   (China)

^b Wuxi Professional College of Science and Technology   (China)

Author keywords

dead zone; Nonlinear system; parameter estimation; saturation; system identification; Wiener model

Indexed keywords

DEAD-ZONE; DEAD-ZONE NONLINEARITY; IDENTIFICATION MODEL; IDENTIFICATION PROBLEM; ITERATIVE ALGORITHM; ITERATIVE IDENTIFICATION; ITERATIVE TECHNIQUE; WIENER MODELS;

ALGORITHMS; IDENTIFICATION (CONTROL SYSTEMS); NONLINEAR SYSTEMS; PARAMETER ESTIMATION; SATURATION (MATERIALS COMPOSITION); SWITCHING FUNCTIONS;

ITERATIVE METHODS;

EID: 84893704037     PISSN: 10775463     EISSN: 17412986     Source Type: Journal    
DOI: 10.1177/1077546312466563     Document Type: Article

References (49)

1. Bai EW. An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems. Automatica. 1998 ; 34 (3). 333-338
2. Bai EW. Identification of linear systems with hard input nonlinearities of known structure. Automatica. 2002 ; 38 (5). 853-860
3. Chen J, Lv LX, Ding RF. Multi-innovation stochastic gradient algorithms for dual-rate sampled systems with preload nonlinearity. Applied Mathematics Letters. 2012a ;:
4. Chen J, Wang XP, Ding RF. Gradient based estimation algorithm for Hammerstein systems with saturation and dead-zone nonlinearities. Applied Mathematical Modelling. 2012b ; 36 (1). 238-243
5. Chen J, Zhang Y, Ding RF. Auxiliary model based multi-innovation algorithms for multivariable nonlinear systems. Mathematical and Computer Modelling. 2010 ; 52 (9-10). 1428-1434
6. Chen J, Zhang Y, Ding F. Gradient based iterative algorithm for Wiener systems with piece-wise nonlinearities using analytic parameterization methods. Computers and Applied Chemistry. 2011a ; 28 (7). 855-857
7. Chen J, Zhang Y, Ding F. Least squares based iterative parameter estimation for output nonlinear systems with piece-wise nonlinearities. Proceedings of the 30th Chinese Control Conference ; 2011b ; 2011b. 1438.
8. Ding F. Several multi-innovation identification methods. Digital Signal Processing. 2010 ; 20 (4). 1027-1039
9. Ding F. Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling. Applied Mathematical Modelling. 2012 ;:
10. Ding F, Chen T. Identification of Hammerstein nonlinear ARMAX systems. Automatica. 2005a ; 41 (9). 1479-1489
11. Ding F, Chen T. Hierarchical identification of lifted state-space models for general dual-rate systems. IEEE Transactions on Circuits and Systems-I: Regular Papers. 2005b ; 52 (6). 1179-1187
12. Ding F, Chen T. Hierarchical least squares identification methods for multivariable systems. IEEE Transactions on Automatic Control. 2005c ; 50 (3). 397-402
13. Ding F, Chen T. Hierarchical gradient-based identification of multivariable discrete-time systems. Automatica. 2005d ; 41 (2). 315-325
14. Ding F, Chen T. Performance analysis of multi-innovation gradient type identification methods. Automatica. 2007 ; 43 (1). 1-14
15. Ding F, Ding J. Least squares parameter estimation with irregularly missing data. International Journal of Adaptive Control and Signal Processing. 2010 ; 24 (7). 540-553
16. Ding J, Ding F. Bias compensation based parameter estimation for output error moving average systems. International Journal of Adaptive Control and Signal Processing. 2011 ; 25 (12). 1100-1111
17. Ding J, Ding F, Liu XP, et al. Hierarchical least squares identification for linear SISO systems with dual-rate sampled-data. IEEE Transactions on Automatic Control. 2011a ; 56 (11). 2677-2683
18. Ding J, Han LL, Chen XM. Time series AR modeling with missing observations based on the polynomial transformation. Mathematical and Computer Modelling. 2010a ; 51 (5-6). 527-536
19. Ding F, Liu YJ, Bao B. Gradient based and least squares based iterative estimation algorithms for multi-input multi-output systems. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. 2012 ; 226 (1). 43-55
20. Ding F, Liu XP, Liu G. Auxiliary model based multi-innovation extended stochastic gradient parameter estimation with colored measurement noises. Signal Processing. 2009a ; 89 (10). 1883-1890
21. Ding F, Liu XP, Liu G. Gradient based and least-squares based iterative identification methods for OE and OEMA systems. Digital Signal Processing. 2010b ; 20 (3). 664-677
22. Ding F, Liu G, Liu XP. Parameter estimation with scarce measurements. Automatica. 2011b ; 47 (8). 1646-1655
23. Ding F, Liu XP, Liu G. Identification methods for Hammerstein nonlinear systems. Digital Signal Processing. 2011c ; 21 (2). 215-238
24. Ding F, Liu XP, Yang HZ. Parameter identification and intersample output estimation for dual-rate systems. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans. 2008 ; 38 (4). 966-975
25. Ding F, Qiu L, Chen T. Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems. Automatica. 2009b ; 45 (2). 324-332
26. Ding F, Shi Y, Chen T. Auxiliary model-based least-squares identification methods for Hammerstein output-error systems. Systems & Control Letters. 2007 ; 56 (5). 373-380
27. Han LL, Ding F. Multi-innovation stochastic gradient algorithms for multi-input multi-output systems. Digital Signal Processing. 2009 ; 19 (4). 545-554
28. Li JH, Ding F. Maximum likelihood stochastic gradient estimation for Hammerstein systems with colored noise based on the key term separation technique. Computers and Mathematics with Applications. 2011 ; 62 (11). 4170-4177
29. Li JH, Ding F, Yang GW. Maximum likelihood least squares identification method for input nonlinear finite impulse response moving average systems. Mathematical and Computer Modelling. 2012 ; 55 (3-4). 442-450
30. Liu YJ, Sheng J, Ding RF. Convergence of stochastic gradient estimation algorithm for multivariable ARX-like systems. Computers and Mathematics with Applications. 2010a ; 59 (8). 2615-2627
31. Liu YJ, Wang DQ, Ding F. Least-squares based iterative algorithms for identifying Box-Jenkins models with finite measurement data. Digital Signal Processing. 2010b ; 20 (5). 1458-1467
32. Liu YJ, Xiao YS, Zhao XL. Multi-innovation stochastic gradient algorithm for multiple-input single-output systems using the auxiliary model. Applied Mathematics and Computation. 2009a ; 215 (4). 1477-1483
33. Liu YJ, Xie L, Ding F. An auxiliary model based recursive least squares parameter estimation algorithm for non-uniformly sampled multirate systems. Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering. 2009b ; 223 (4). 445-454
34. Shi Y, Chen T. Optimal design of multi-channel transmultiplexers with stopband energy and passband magnitude constraints. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing. 2003 ; 50 (9). 659-662
35. Shi Y, Ding F, Chen T. Multirate crosstalk identification in xDSL systems. IEEE Transactions on Communications. 2006 ; 54 (10). 1878-1886
36. Shi Y, Fang H. Kalman filter based identification for systems with randomly missing measurements in a network environment. International Journal of Control. 2010 ; 33 (3). 538-551
37. Shi Y, Fang H, Yan M. Kalman filter based adaptive control for networked systems with unknown parameters and randomly missing outputs. International Journal of Robust and Nonlinear Control, Special Issue on Control with Limited Information (Part II). 2009 ; 19 (18). 1976-1992
38. Vörös J. Parameter identification of Wiener systems with discontinuous nonlinearities. Systems and Control Letters. 2001 ; 44 (5). 363-372
39. Vörös J. Modeling and parameter identification of systems with multisegment piecewise-linear characteristics. IEEE Transactions on Automatic control. 2002 ; 47 (1). 184-188
40. Vörös J. Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearities. Systems and Control Letters. 2007 ; 56 (2). 99-105
41. Vörös J. Modeling and identification of systems with backlash. Automatica. 2010 ; 46 (2). 369-374
42. Wang DQ, Ding F. Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems. Computers and Mathematics with Applications. 2008 ; 56 (12). 3157-3164
43. Wang DQ, Ding F. Performance analysis of the auxiliary models based multi-innovation stochastic gradient estimation algorithm for output error systems. Digital Signal Processing. 2010 ; 20 (3). 750-762
44. Wang DQ, Ding F. Least squares based and gradient based iterative identification for Wiener nonlinear systems. Signal Processing. 2011 ; 91 (5). 1182-1189
45. Xiao YS, Yue N. Parameter estimation for nonlinear dynamical adjustment models. Mathematical and Computer Modelling. 2011 ; 54 (5-6). 1561-1568
46. Xie L, Liu YJ, Yang HZ, et al. Modeling and identification for non-uniformly periodically sampled-data systems. IET Control Theory and Applications. 2010 ; 4 (5). 784-794
47. Xie L, Yang HZ. Gradient based iterative identification for non-uniform sampling output error systems. Journal of Vibration and Control. 2011 ; 17 (3). 471-478
48. Yu B, Fang H, Lin Y, et al. Identification of Hammerstein output-error systems with two-segment nonlinearities: algorithm and applications. Control and Intelligent Systems. 2010 ; 38 (4). 194-201
49. Zhang JB, Ding F, Shi Y. Self-tuning control based on multi-innovation stochastic gradient parameter estimation. Systems and Control Letters. 2009 ; 58 (1). 69-75