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4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems. (English) Zbl 0787.93097

Summary: Recently a great deal of attention has been given to numerical algorithms for subspace state space system identification (N4SID). In this paper, we derive two new N4SID algorithms to identify mixed deterministic- stochastic systems. Both algorithms determine state sequences through the projection of input and output data. These state sequences are shown to be outputs of non-steady state Kalman filter banks. From these it is easy to determine the state space system matrices. The N4SID algorithms are always convergent (non-iterative) and numerically stable since they only make use of QR and Singular Value Decompositions. Both N4SID algorithms are similar, but the second one trades of accuracy for simplicity. These new algorithms are compared with existing subspace algorithms in theory and in practice.

MSC:

93E12 Identification in stochastic control theory
Full Text: DOI

References:

[1] Anderson, B. D.O; Moore, J. B., Optimal Filtering (1979), Prentice-Hall: Prentice-Hall Englewood Cliffs, NJ · Zbl 0758.93070
[2] Arun, K. S.; Kung, S. Y., Balanced approximation of stochastic systems, SIAM J. Matrix Analysis and Applications, 11, 42-68 (1990) · Zbl 0698.93084
[3] Backx, T., Identification of an industrial process: a Markov parameter approach, (Doctoral Dissertation (1987), Technical University Eindhoven: Technical University Eindhoven The Netherlands)
[4] De Moor, B., Mathematical concepts and techniques for modeling of static and dynamic systems, (Doctoral Dissertation (1988), Department of Electrical Engineering, Kath. Universiteit Leuven: Department of Electrical Engineering, Kath. Universiteit Leuven Belgium)
[5] De Moor, B.; Van Overschee, P.; Suykens, J., Subspace algorithms system identification and stochastic realization, (Proceedings MTNS. Proceedings MTNS, Kobe, Japan (1991)), 589-594, part 1
[6] Enns, D., Model reduction for control system design, (Ph.D., dissertation (1984), Dep. Aeronaut. Astronaut., Stanford University: Dep. Aeronaut. Astronaut., Stanford University Stanford, CA)
[7] Faure, P., Stochastic realization algorithms, (Mehra, R.; Lainiotis, D., System Identification: Advances and Case Studies (1976), Academic Press: Academic Press NY)
[8] Kailath, T., Linear Systems (1980), Prentice-Hall: Prentice-Hall Englewood Cliffs, NJ · Zbl 0458.93025
[9] Kung, S. Y., A new identification and model reduction algorithm via singular value decomposition, (Proc. of the 12th Asilomar Conference on Circuits, Systems and Computers. Proc. of the 12th Asilomar Conference on Circuits, Systems and Computers, Pacific Grove (1978)), 705-714
[10] Larimore, W. E., Canonical variate analysis in identification, filtering, and adaptive control, (Proceedings of the IEEE 29th Conf. on Decision and Control. Proceedings of the IEEE 29th Conf. on Decision and Control, Hawaii (1990)), 596-604
[11] Ljung, L., System Identification: Theory for the User (1987), Prentice-Hall Information and System Sciences Series: Prentice-Hall Information and System Sciences Series Englewood Cliffs, NJ · Zbl 0615.93004
[12] Ljung, L., System Identification Toolbox (1991), The Mathworks, Inc.
[13] Moonen, M.; De Moor, B.; Vandenberghe, L.; Vandewalle, J., On- and off-line identification of linear state space models, International Journal of Control, 49, 219-232 (1989) · Zbl 0661.93072
[14] Moonen, M.; Ramos, J., A subspace algorithm for balanced state space system identification, (ESAT/SISTA report 1991-07 (1991), Kath. Universiteit Leuven, Dept. E.E.,: Kath. Universiteit Leuven, Dept. E.E., Belgium), Accepted for publication in IEEE Automatic Control (to appear 1993). · Zbl 0795.93028
[15] Moonen, M.; Van Overschee, P.; De Moor, B., A Subspace Algorithm for Combined Stochastic-Deterministic State Space Identification, (ESAT/SISTA report 1992-10 (1992), Kath. Universiteit Leuven, Dept. E.E.,: Kath. Universiteit Leuven, Dept. E.E., Belgium)
[16] Papoulis, A., Probability, Random Variables, and Stochastic Processes (1984), McGraw-Hill: McGraw-Hill NY · Zbl 0191.46704
[17] Van Overschee, P.; De Moor, B., Subspace algorithms for the stochastic identification problem, (30th IEEE Conference On Decision and Control. 30th IEEE Conference On Decision and Control, Brighton, U.K. (1991)), 1321-1326
[18] Van Overschee, P.; De Moor, B., Subspace Algorithms for the Stochastic Identification Problem, (ESAT/SISTA report 1991-26. ESAT/SISTA report 1991-26, Automatica, 29 (1991)), 649-660, Kath. Universiteit Leuven, Dept. E.E., Belgium · Zbl 0771.93082
[19] Van Overschee, P.; De Moor, B., Two Subspace Algorithms for the Identification of Combined deterministic-Stochastic Systems, (ESAT/SISTA report 1992-34 (1992), Kath. Universiteit Leuven, Dept. E.E.,: Kath. Universiteit Leuven, Dept. E.E., Belgium) · Zbl 0787.93097
[20] Verhaegen, M., A novel non-iterative MIMO state space model identification technique, (Preprints 9th IFAC/IFORS symposium on Identification and System parameter estimation. Preprints 9th IFAC/IFORS symposium on Identification and System parameter estimation, Budapest, Hungary (1991)), 1453-1458
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