Skip to main content
Log in

Numerical computation of H optimal performance

  • Published:
Journal of Scientific Computing Aims and scope Submit manuscript

Abstract

We present new algorithms for computing theH optimal performance for a class of single-input/single-output (SISO) infinite-dimensional systems. The algorithms here only require use of one or two fast Fourier transforms (FFT) and Cholesky decompositions; hence the algorithms are particularly simple and easy to implement. Numerical examples show that the algorithms are stable and efficient and converge rapidly. The method has wide applications including to theH optimal control of distributed parameter systems. We illustrate the technique with applications to some delay problems and a partial differential equation (PDE) model. The algorithms we present are also an attractive approach to the solution of high-order finite-dimensional models for which use of state space methods would present computational difficulties.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ball, J. A., Helton, J. W.(1983). A Beurling-Lax theorem for the Lie groupu(m,n) which contains most classical interpolation theory,J. Operator Theory 9(1), 107–142.

    Google Scholar 

  • Clough, R. W., and Penzien, J. (1975).Dynamics of Structures, McGraw-Hill, New York.

    Google Scholar 

  • Doyle, J. C., and Stein, G. (1980). Multivariable feedback design: Concepts for a classical/ modern synthesis,IEEE Trans. Automatic Control AC-26(1), 4–16.

    Google Scholar 

  • Fagnani, F. (1991). An operator-theoretic approach to the mixed-sensitivity minimization problem,Syst. Control Lett. 17, 227–235.

    Google Scholar 

  • Flamm, D. S. (1986). Control of Delay Systems for Minimax Sensitivity, Technical Report No. LIDS-TH-1560, Massachusetts Institute of Technology Laboratory for Information and Decision Systems.

  • Flamm, D. S. (1990). A Model of a Damped Flexible Beam, ISS Report No. 54, Department of Electrical Engineering, Princeton University.

  • Flamm, D. S. and Yang, H. (1990). Optimal mixed sensitivity for general distributed plants, to appear inIEEE Trans. Automatic Control.

  • Foias, C., Tannenbaum, A., and Zames, G. (1986). Weighted sensitivity minimization for delay systems,IEEE Trans. Automatic Control AC-31(8), 763–766.

    Google Scholar 

  • Francis, B., Helton, J. W., and Zames, G. (1984).H -optimal feedback controllers for linear multivariable systems,IEEE Trans. Automatic Control AC-29(10), 888–900.

    Google Scholar 

  • Francis, B. A. (1987). A Course inH Control Theory, Springer-Verlag, New York.

    Google Scholar 

  • Hoffman, K. (1962).Banach Spaces of Analytic Functions, Prentice-Hall, Englewood Cliffs, New Jersey.

    Google Scholar 

  • Orszag, J. M., and Yang, H. (1992). Portfolio Choice with Knightian Uncertainty, Department of Economics, University of Michigan.

  • Rosenblum, M., and Rovnyak, J. (1985).Hardy Classes and Operator Theory, Oxford University Press, Oxford.

    Google Scholar 

  • Safonov, M. G., Laub, A. J., and Hartmann, G. (1980). Feedback properties of multivariable systems: The role and use of the return difference matrix,IEEEE Trans. Automatic Control AC-26(1), 47–65.

    Google Scholar 

  • Sarason, D. (1985). Operator-theoretic aspects of the Nevanlinna-Pick interpolation problem, inOperator and Function Theory, pages 279–314, 1985.

  • Yang, H. (1993). 311–03 optimal compensators for a class of infinite dimensional systems, submitted toAmerican Control Conference 1993.

  • Yang, H. (1992). Frequency domain method forH optimal mixed sensitivity design, manuscript.

  • Yang, H., and Flamm, D. S. (1990). Mixed sensitivity design for a class of multivariable infinite dimensional systems. Submitted toIEEE Transactions on Automatic Control.

  • Yang, H., and Orszag, J. M. (1992). Spectral and nonparametric optimization methods for portfolio choice. Princeton University Program in Applied and Computational Mathematics, October 1992.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yang, H., Orszag, J.M. Numerical computation of H optimal performance. J Sci Comput 7, 289–311 (1992). https://doi.org/10.1007/BF01108034

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01108034

Key words

Navigation