Online identification of a drifting system using generalised Kalman filtering

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Online identification of a drifting system using generalised Kalman filtering

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© The Institution of Electrical Engineers
Published

The letter describes an online method for the identification of drifting parameters of a sampled-data system. The model used describes both the plant and the noise.

Inspec keywords: identification; filtering and prediction theory; sampled data systems

Other keywords: drifting system; plant description; Kalman filtering; sampled data system; online identification; noise description

Subjects: Simulation, modelling and identification; Discrete control systems

References

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      • J.B. Farisen . Parameter identification for a class of linear discrete systems. IEEE Trans.
    2. 2)
      • Bryson, A.E., Johansen, D.E.: `Linear filtering for time-varying systems using measurements containing colored noise', Research report 384, Applied Research Lab., January 1964.
    3. 3)
      • D.Q. Mayne . Optimal non-stationary estimation of the parameters of a linear system with Gaussian inputs. J. Electron. Control , 101 - 112
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      • J. Peschon . (1965) , Disciplines and techniques of system control.
    5. 5)
      • T. Bohlin . Real-time estimation of time-variable process characteristics. IBM TP
    6. 6)
      • R. Hastings-James , M.W. Sage . Recursive generalised-least-squares procedure for online identification of process parameters. Proc. IEE , 2057 - 2062
    7. 7)
      • Clarke, D.W.: `Generalized least squares estimation of the parameters of a dynamic model', paper 317, Identification in automatic control systems, Prague, IFAC symposium.
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