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Box–Jenkins model LQG controller: design and performance

Box–Jenkins model LQG controller: design and performance

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The relationship between the variances of the input and output variables of a Box–Jenkins model control system under the linear quadratic Gaussian control law is obtained. This relationship is generalised to the relationships between the statistics of the input and output variables under this control law. Formulae to calculate these statistics are derived. The statistics are the auto-covariances and cross-covariances of the two input and output variable time series driven by the same Gaussian white noise. The statistics can be used to assess control loop performance.

References

    1. 1)
      • J.F. MACGREGOR . Optimal discrete stochastic control theory for process applications. Can. J. Chem. Eng. , 468 - 478
    2. 2)
      • K.J. Åström . (1970) , Introduction to stochastic control theory.
    3. 3)
      • K. VU . Optimal setting for discrete PID controller. Proc. IEE , 31 - 40
    4. 4)
      • K. VU . Determination of the penalty constant for discrete constrained linear quadratic Gaussian controller design. Int. J. Syst. Sci. , 4 , 713 - 721
    5. 5)
      • K.J. Åström , B. Wittenmark . (1989) , Adaptive control.
    6. 6)
      • K.J. ÅSTRÖM . Assessment of achievable performance of simple feedback loops. Int. J. Adapt. Control , 3 - 19
    7. 7)
      • J.F. MACGREGOR , J.D. WRIGHT , M.H. HUYNH . Optimal tuning of digital PID controllers using dynamic-stochastic models. IEC Process Des. Dev. , 398 - 402
    8. 8)
      • L.D. Desborough , T.J. Harris . Performance assessment measures for univariate feedback control. Can. J. Chem. Eng. , 1186 - 1197
    9. 9)
      • T.J. Harris . Assessment of control loop performance. Can. J. Chem. Eng. , 856 - 861
    10. 10)
      • W.W.S. WEI . (1990) , Time series analysis—Univariate and multivariate methods.
    11. 11)
      • K. VU , G. DUMONT , P. TESSIER . Recursive least determinant self-tuning regulator. Proc. IEE , 285 - 292
    12. 12)
      • K. VU . Linear time series variance. Int. J. Control. , 5 , 1291 - 1297
    13. 13)
      • K. VU . Variance formulae for feedback stochastic control system. Int. J. Syst. Sci. , 4 , 489 - 501
    14. 14)
      • E. MOSCA . (1995) , Optimal, predictive and adaptive control.
    15. 15)
      • F.G. SHINSKEY . Putting controllers to the test. Chem. Eng. , 96 - 106
    16. 16)
      • M.J. GRIMBLE . Implicit and explicit LQG self-tuning controllers. Automatica , 661 - 669
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