A novel APSO-aided maximum likelihood identification method for Hammerstein systems

Nonlinear Dynamics

Volumn 73, Issue 1-2, 2013, Pages 449-462

  Sun, Jianliang ^a   Liu, Xinggao ^a  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

Author keywords

Adaptive particle swarm optimization; Hammerstein system; Maximum likelihood principle

Indexed keywords

ADAPTIVE PARTICLE SWARM OPTIMIZATIONS; HAMMERSTEIN SYSTEM; IMPLEMENTATION AND COMPUTATION; MAXIMUM LIKELIHOOD ESTIMATE; MAXIMUM LIKELIHOOD ESTIMATOR; MAXIMUM LIKELIHOOD PRINCIPLE; MULTIDIMENSIONAL OPTIMIZATION; RECURSIVE LEAST SQUARE METHODS;

ALGORITHMS; LINEAR SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION; PARTICLE SWARM OPTIMIZATION (PSO);

NONLINEAR SYSTEMS;

EID: 84879786382     PISSN: 0924090X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11071-013-0800-4     Document Type: Article

References (42)

1. Bai, E.W.: Decoupling the linear and nonlinear parts in Hammerstein model identification. Automatica 40, 671-676 (2007)
2. Vanbeylen, L., Pintelon, R., Schoukens, J.: Blind maximum likelihood identification of Hammerstein systems. Automatica 44, 3139-3146 (2008)
3. Ding, F., Liu, X.P., Liu, G.: Identification methods for Hammerstein nonlinear systems. Digit. Signal Process. 21, 215-238 (2012)
4. Wang, D.Q., Ding, F.: Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems. Comput. Math. Appl. 56, 3157-3164 (2008)
5. Ding, F., Shi, Y., Chen, T.: Auxiliary model based least-square identification methods for Hammerstein output error systems. Syst. Control Lett. 56, 373-380 (2007)
6. Liu, X., Qian, J.: Modeling, control and optimization of ideal internal thermally coupled distillation columns. Chem. Eng. Technol. 23, 235-241 (2000)
7. Chen, Y., Liu, X.: Modeling mass transport of propylene polymerization on Ziegler-Natta catalyst. Polymer 46, 9434-9442 (2005)
8. Wang, D.Q., Ding, F.: Least squares based and gradient based iterative identification for Wiener nonlinear systems. Signal Process. 91, 1182-1189 (2011)
9. Li, J., Ding, F., Yang, G.: Maximum likelihood least squares identification method for input nonlinear finite impulse response moving average systems. Math. Comput. Model. 55, 442-450 (2012)
10. Zhu, Y., Liu, X.: Dynamics and control of high purity heat integrated distillation columns. Ind. Eng. Chem. Res. 44, 8806-8814 (2005)
11. Ding, F., Shi, Y., Chen, T.: Gradient-based identification methods for Hammerstein nonlinear ARMAX models. Nonlinear Dyn. 45, 31-43 (2005)
12. Narendra, K., Gallman, P.: An iterative method for the identification of nonlinear systems using a Hammerstein model. IEEE Trans. Autom. Control 11, 546-550 (1966)
13. Vörös, J.: Recursive identification of Hammerstein systems with discontinuous nonlinearities containing dead-zones. IEEE Trans. Autom. Control 48, 2203-2206 (2003)
14. Ding, F., Chen, T.: Identification of Hammerstein nonlinear ARMAX systems. Automatica 41, 1479-1489 (2005)
15. Yu, B., Fang, H., Lin, Y., Shi, Y.: Identification of Hammerstein output-error systems with two-segment nonlinearities: algorithm and applications. Control Intell. Syst. 38, 194-201 (2010)
16. Liu, Y., Xiao, Y., Zhao, X.: Multi-innovation stochastic gradient algorithm for multiple-input single-output systems using the auxiliary model. Appl. Math. Comput. 215, 1477-1483 (2009)
17. Liu, Y., Sheng, J., Ding, R.: Convergence of stochastic gradient estimation algorithm for multivariable ARX-like systems. Comput. Math. Appl. 59, 2615-2627 (2010)
18. Ding, F., Liu, G., Liu, X.: Parameter estimation with scarce measurements. Automatica 47, 1646-1655 (2011)
19. Ding, F.: Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling. Appl. Math. Model. 37, 1694-1704 (2013)
20. LL-Duwaish, H., Karim, M.: A new method for the identification of Hammerstein Model. Automatica 33, 1871-1875 (1997)
21. Lang, Z.: A nonparametric polynomial identification algorithm for the Hammerstein system. IEEE Trans. Autom. Control 42, 1435-1441 (1997)
22. Wang, J., Sano, A., Chen, T., Huang, B.: Identification of Hammerstein systems without explicit parameterization of non-linearity. Int. J. Control 82, 937-952 (2009)
23. Chen, C.H., Fassois, S.D.: Maximum likelihood identification of stochastic Wiener-Hammerstein-type non-linear systems. Mech. Syst. Signal Process. 6, 135-153 (1992)
24. Ljung, L.: System Identification: Theory for the User. Prentice Hall, Englewood Cliffs (1987)
25. Hagenblad, A., Ljung, L.: Maximum likelihood identification of Wiener models. Automatica 44, 2697-2705 (2008)
26. Chen, S., Hong, X., Harris, C.J.: Particle swarm optimization aided orthogonal forward regression of unified data modeling. IEEE Trans. Evol. Comput. 14, 477-499 (2010)
27. Konstantinos, T., Grigorios, B., Spiridon, L.: Combining evolutionary and stochastic gradient techniques for system identification. J. Comput. Appl. Math. 2(27), 147-160 (2009)
28. Bai, E.W.: An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems. Automatica 34, 333-338 (1998)
29. Chang, F., Luus, R.: A noniterative method for identification using Hammerstein model. IEEE Trans. Autom. Control 16, 464-468 (1971)
30. Bai, E.W.: A blind approach to the Hammerstein-Wiener model identification. Automatica 38, 967-979 (2002)
31. Astrom, K.J.: Maximum likelihood and prediction error methods. Automatica 16, 551-574 (1980)
32. Wang, W., Ding, F., Dai, J.: Maximum likelihood least squares identification for systems with autoregressive moving average noise. Appl. Math. Model. 36, 1842-1853 (2012)
33. Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, pp. 39-43 (1995)
34. Shi, Y., Eberhart, R.: Fuzzy adaptive particle swarm optimization. In: Proceedings of the 2001 Congress on Evolutionary Computation, pp. 101-106 (2001)
35. Clerc, M., Kennedy, J.: The particle swarm - explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6, 58-73 (2002)
36. Kadirkamanathan, V., Selvarajah, K., Fleming, P.J.: Stability analysis of the particle dynamics in particle swarm optimizer. IEEE Trans. Evol. Comput. 10, 245-255 (2006)
37. Trelea, I.C.: The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf. Process. Lett. 85, 317-325 (2003)
38. Kennedy, J., Mendes, R.: Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms. In: Proceedings of the 2003 IEEE SMC Workshop on Soft Computing in Industrial Applications (SMCia03), Binghamton, New York (2003)
39. Suganthan, P.N.: Particle swarm optimizer with neighborhood operator. In: Proceedings of the 1999 Congress on Evolutionary Computation, vol. 3, pp. 1958-1962 (1999)
40. Ratnaweera, A., Halgamuge, S.K., Watson, H.C.: Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Trans. Evol. Comput. 8, 240-255 (2004)
41. Zhan, Z.H., Zhang, J., Li, Y., Chung, H.S.: Adaptive particle swarm optimization. IEEE Trans. Syst. Man Cybern., Part B 39, 1362-1381 (2009)
42. Liu, X., Lu, J.: Least squares based iterative identification for a class of multirate systems. Automatica 46, 549-554 (2010)