Multi-mode system identification

The subspace identification method for time-invariant linear systems is extended to the class of multi-mode or hybrid systems. Under an excitation criterion, the parameters in all modes are simultaneously estimated, and combined with a detection scheme for the mode switching. In turn, parameters of the mode switching mechanism, whether deterministic or Markovian, can be estimated as well. The method is readily applicable to fault detection and identification.

[1]  John B. Moore,et al.  Hidden Markov Models: Estimation and Control , 1994 .

[2]  John B. Moore,et al.  On-line identification of hidden Markov models via recursive prediction error techniques , 1994, IEEE Trans. Signal Process..

[3]  I︠a︡. Z. T︠S︡ypkin,et al.  Foundations of the theory of learning systems , 1973 .

[4]  L. Mevel,et al.  Recursive identification of HMMs with observations in a finite set , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[5]  V. Wertz,et al.  Adaptive Optimal Control: The Thinking Man's G.P.C. , 1991 .

[6]  Sabine Van Huffel,et al.  Total least squares problem - computational aspects and analysis , 1991, Frontiers in applied mathematics.

[7]  James D. Hamilton Time Series Analysis , 1994 .

[8]  Alan S. Willsky,et al.  A survey of design methods for failure detection in dynamic systems , 1976, Autom..

[9]  Manfred Morari,et al.  Change detection using non-linear filtering and likelihood ratio testing , 1997, 1997 European Control Conference (ECC).

[10]  Thomas Kailath,et al.  Linear Systems , 1980 .

[11]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

[12]  Jakow Salmanowitzsch Zypkin,et al.  Adaption und Lernen in kybernetischen Systemen , 1970 .

[13]  Brian D. O. Anderson,et al.  New Developments in the Theory of Positive Systems , 1997 .

[14]  Kumpati S. Narendra,et al.  Adaptive control of discrete-time systems using multiple models , 2000, IEEE Trans. Autom. Control..

[15]  Michèle Basseville,et al.  Detecting changes in signals and systems - A survey , 1988, Autom..

[16]  Paul M. Frank,et al.  Issues of Fault Diagnosis for Dynamic Systems , 2010, Springer London.

[17]  E. I. Verriest,et al.  A 2-D realization theory for Markov chains , 1990, 29th IEEE Conference on Decision and Control.

[18]  Sabine Van Huffel,et al.  The total least squares problem , 1993 .

[19]  Kumpati S. Narendra,et al.  Adaptive control using multiple models , 1997, IEEE Trans. Autom. Control..

[20]  Michel Gevers,et al.  Towards a Joint Design of Identification and Control , 1993 .

[21]  Michael Athans,et al.  Analysis of gain scheduled control for nonlinear plants , 1990 .

[22]  Gang Tao,et al.  Adaptive Control of Systems with Actuator and Sensor Nonlinearities , 1996 .

[23]  Michèle Basseville,et al.  Detection of Abrupt Changes in Signals and Dynamical Systems , 1985 .

[24]  B. Pasik-Duncan,et al.  Adaptive Control , 1996, IEEE Control Systems.

[25]  H. Tong Non-linear time series. A dynamical system approach , 1990 .

[26]  C. Byrnes,et al.  Systems and Control in the Twenty-First Century , 1997 .

[27]  John B. Moore,et al.  On-line estimation of hidden Markov model parameters based on the Kullback-Leibler information measure , 1993, IEEE Trans. Signal Process..

[28]  Rolf Isermann,et al.  Process fault detection based on modeling and estimation methods - A survey , 1984, Autom..

[29]  Rolf Isermann,et al.  Fault diagnosis of machines via parameter estimation and knowledge processing - Tutorial paper , 1991, Autom..

[30]  Bart De Moor,et al.  Numerical algorithms for state space subspace system identification , 1993 .

[31]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .

[32]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems: theory and application , 1989 .

[33]  Petre Stoica,et al.  Decentralized Control , 2018, The Control Systems Handbook.

[34]  W. H. Chung,et al.  A game theoretic fault detection filter , 1998, IEEE Trans. Autom. Control..

[35]  M. Mariton,et al.  Jump Linear Systems in Automatic Control , 1992 .