Modified subspace identification for periodically non-uniformly sampled systems by using the lifting technique

Circuits, Systems, and Signal Processing

Volumn 33, Issue 5, 2014, Pages 1439-1449

  Ding, Jie ^a   Lin, Jinxing ^a  

^a NANJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Casuality constraint; Lifting technique; Non uniform sampling; Parameter estimation; Subspace identification

Indexed keywords

DIGITAL CONTROL SYSTEMS; PARAMETER ESTIMATION;

CASUALITIES; DISCRETE TIME SYSTEM; IDENTIFICATION PROBLEM; LIFTING TECHNIQUES; NONUNIFORM SAMPLING; STATE-SPACE MODELING; SUBSPACE IDENTIFICATION; SUBSPACE IDENTIFICATION METHODS;

DISCRETE TIME CONTROL SYSTEMS;

EID: 84900556855     PISSN: 0278081X     EISSN: 15315878     Source Type: Journal    
DOI: 10.1007/s00034-013-9704-2     Document Type: Article

References (35)

1. F. Ding, System Identification - New Theory and Methods (Science Press, Beijing, 2013)
2. J. Ding, F. Ding, X.P. Liu, G. Liu, Hierarchical least squares identification for linear SISO systems with dual-rate sampled-data. IEEE Trans. Autom. Control 56(11), 2677-2683 (2011)
3. J. Ding, F. Ding, Bias compensation based parameter estimation for output error moving average systems. Int. J. Adapt. Control Signal Process. 25(12), 1100-1111 (2011)
4. F. Ding, Coupled-least-squares identification for multivariable systems. IET Control Theory Appl. 7(1), 68-79 (2013)
5. F. Ding, Decomposition based fast least squares algorithm for output error systems. Signal Process. 93(5), 1235-1242 (2013)
6. F. Ding, Two-stage least squares based iterative estimation algorithm for CARARMA system modeling. Appl. Math. Model. 37(7), 4798-4808 (2013)
7. F. Ding, X.G. Liu, J. Chu, Gradient-based and least-squares-based iterative algorithms for Hammerstein systems using the hierarchical identification principle. IET Control Theory Appl. 7(2), 176-184 (2013)
8. F. Ding, Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling. Appl. Math. Model. 37(4), 1694-1704 (2013)
9. F. Ding, Combined state and least squares parameter estimation algorithms for dynamic systems. Appl. Math. Model. (2013). doi: 10.1016/j.apm.2013.06.007
10. F. Ding, G. Liu, X.P. Liu, Partially coupled stochastic gradient identification methods for non-uniformly sampled systems. IEEE Trans. Autom. Control 55(8), 1976-1981 (2010)
11. F. Ding, L. Qiu, T. Chen, Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems. Automatica 45(2), 324-332 (2009)
12. F. Ding, Y. Gu, Performance analysis of the auxiliary model-based stochastic gradient parameter estimation algorithm for state space systems with one-step state delay. Circuits Syst. Signal Process. 32(2), 585-599 (2013)
13. F. Ding, J.X. Ma, Y.S. Xiao, Newton iterative identification for a class of output nonlinear systems with moving average noises. Nonlinear Dyn. 74(1-2), 21-30 (2013)
14. Y. Gu, X.L. Lu, R.F. Ding, Parameter and state estimation algorithm for a state space model with a one-unit state delay. Circuits Syst. Signal Process. 32(5), 2267-2280 (2013)
15. M.F. Hassan, M. Zribi, H.M.K. Alazemi, A recursive state estimator in the presence of state inequality constraints. Int. J. Control. Autom. Syst. 9(2), 237-248 (2011)
16. T. Katayama, Subspace Methods for System Identification (Springer, London, 2005)
17. G. Kreisselmeier, On sampling without loss of observability/ controllability. IEEE Trans. Autom. Control 44(5), 1021-1025 (1999)
18. W.H. Li, Z. Han, S.L. Shah, Subspace identification for FDI in systems with non-uniformly sampled multirate data. Automatica 42(4), 619-627 (2006)
19. W.H. Li, S.L. Shah, D.Y. Xiao, Kalman filters in non-uniformly sampled multirate systems: for FDI and beyond. Automatica 44(1), 199-208 (2008)
20. Y.J. Liu, F. Ding, Y. Shi, Least squares estimation for a class of non-uniformly sampled systems based on the hierarchical identification principle. Circuits Syst. Signal Process. 31(6), 1985-2000 (2012)
21. Y.J. Liu, L. Xie, F. Ding, An auxiliary model based recursive least squares parameter estimation algorithm for non-uniformly sampled multirate systems. J. Syst. Control Eng. 223(4), 445-454 (2009)
22. S. López-López, A. Sideris, J. Yu, Two-stage H-infinity optimization approach to multirate controller design. Int. J. Control. Autom. Syst. 10(4), 675-683 (2012)
23. J.X. Ma, F. Ding, Recursive relations of the cost functions for the least squares algorithms for multivariable systems. Circuits Syst. Signal Process. 32(1), 83-101 (2013)
24. E. Muramatsu, M. Ikeda, Parameter and state estimation for uncertain linear systems by multiple observers. Int. J. Control. Autom. Syst. 9(4), 617-626 (2011)
25. P. Qin, S. Kanae, Z. Yang, K. Wada, Identification of lifted models for general dual-rate sampled-data systems using N4SID algorithm. IEEJ Trans. Electron. Inf. Syst. 128(5), 788-794 (2008)
26. J. Sheng, T. Chen, S.L. Shah, Generalized predictive control for non-uniformly sampled systems. J. Process Control 12(8), 875-885 (2002)
27. P. Van Overschee, B. De Moor, Subspace Identification for Linear Systems: Theory, Implementation, Applications (Kluwer Academic, Dordrecht, 1996)
28. L. Wang, P. Cheng, Y. Wang, Frequency domain subspace identification of commensurate fractional order input time delay systems. Int. J. Control. Autom. Syst. 9(2), 310-316 (2011)
29. D.Q. Wang, F. Ding, Hierarchical least squares estimation algorithm for Hammerstein-Wiener systems. IEEE Signal Process. Lett. 19(12), 825-828 (2012)
30. D.Q. Wang, F. Ding, Least squares based and gradient based iterative identification for Wiener nonlinear systems. Signal Process. 91(5), 1182-1189 (2011)
31. D.Q. Wang, F. Ding, Y.Y. Chu, Data filtering based recursive least squares algorithm for Hammerstein systems using the key-term separation principle. Inf. Sci. 222, 203-212 (2013)
32. L. Xie, Y.J. Liu, H.Z. Yang, F. Ding, Modeling and identification for non-uniformly periodically sampled-data systems. IET Control Theory Appl. 4(5), 784-794 (2010)
33. L. Xie, H.Z. Yang, Gradient based iterative identification for non-uniform sampling output error systems. J. Vib. Control 17(3), 471-478 (2011)
34. L. Xie, H.Z. Yang, F. Ding, Recursive least squares parameter estimation for non-uniformly sampled systems based on the data filtering. Math. Comput. Model. 54(1-2), 315-324 (2011)
35. Y. Zhu, H. Telkamp, J. Wang, Q. Fu, System identification using slow and irregular output samples. J. Process Control 19(1), 58-67 (2009)