Use of kernels of bicausal operators in scalar gain-phase predictive control

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Use of kernels of bicausal operators in scalar gain-phase predictive control

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IEE Proceedings D (Control Theory and Applications) — Recommend this title to your library

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© The Institution of Electrical Engineers
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The implementation of the decomposition of linear discrete-time multivariable problems through either singular values/principal directions, or eigenvalues/eigenvectors is inherently anti-causal. One way to avoid this is to introduce a ‘pseudodelay’ into the controller, but this is undesirable. Here the problem is examined in the scalar case, and a new algorithm proposed which deploys a kernel to characterise all the available degrees of freedom, and thus overcome completely the problems of delay and anticausality.

Inspec keywords: eigenvalues and eigenfunctions; predictive control; discrete time systems; multivariable control systems

Other keywords: anticausality; degrees of freedom; delay; singular values/principal directions; decomposition; eigenvalues/eigenvectors; bicausal operators; scalar gain-phase predictive control; linear discrete-time multivariable problems

Subjects: Optimal control; Discrete control systems; Multivariable control systems

References

    1. 1)
      • B. Kouvaritakis , J.A. Rossiter , A.O.T. Chang . A singular value decomposition approach to multivariable generalized predictive control. IEE Proc.-D
    2. 2)
      • D.W. Clark , C. Mohtadi , P.S. Tuffs . Generalized predictive control. Automatica , 137 - 148
    3. 3)
      • B. Kouvaritakis , J.A. Rossiter . Bi-causal representations and multivariable generalized predictive control. Automatica , 819 - 828
    4. 4)
      • B. Kouvaritakis , J.A. Rossiter , A.O.T. Chang . Gain phase decomposition and generalized predictive control of scalar systems. Proc. IEE Pt.-D , 1 , 97 - 105
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