Skip to main content

Optimal Sampled-Data Control

  • 385 Accesses

Abstract

This article gives a brief overview on the modern development of sampled-data control. Sampled-data systems intrinsically involve a mixture of two different time sets, one continuous and the other discrete. Due to this, sampled-data systems cannot be characterized in terms of the standard notions of transfer functions, steady-state response, or frequency response. The technique of lifting resolves this difficulty and enables the recovery of such concepts and simplified solutions to sampled-data H and H 2 optimization problems. We review the lifting point of view, its application to such optimization problems, and finally present an instructive numerical example.

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

Bibliography

  • Åström KJ, Wittenmark B (1996) Computer controlled systems—theory and design, 3rd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Bamieh B, Pearson JB (1992) A general framework for linear periodic systems with applications to H sampled-data control. IEEE Trans Autom Control 37:418–435

    Article  MATH  MathSciNet  Google Scholar 

  • Bamieh B, Pearson JB, Francis BA, Tannenbaum A (1991) A lifting technique for linear periodic systems with applications to sampled-data control systems. Syst Control Lett 17:79–88

    Article  MATH  MathSciNet  Google Scholar 

  • Cantoni M, Glover K (1997) H sampled-data synthesis and related numerical issues. Automatica 33:2233–2241

    Article  MATH  MathSciNet  Google Scholar 

  • Chen T, Francis BA (1990) On the \(\mathcal{L}_{2}\)-induced norm of a sampled-data system. Syst Control Lett 15:211–219

    Article  MATH  MathSciNet  Google Scholar 

  • Chen T, Francis BA (1995) Optimal sampled-data control systems. Springer, New York

    Book  MATH  Google Scholar 

  • Jury EI (1958) Sampled-data control systems. Wiley, New York

    MATH  Google Scholar 

  • Kabamba PT, Hara S (1993) Worst case analysis and design of sampled data control systems. IEEE Trans Autom Control 38:1337–1357

    Article  MATH  MathSciNet  Google Scholar 

  • Nagahara M, Yamamoto, Y (2012) Frequency domain min-max optimization of noise-shaping Delta-Sigma modulators. IEEE Trans Signal Process 60:2828–2839

    Article  MathSciNet  Google Scholar 

  • Ragazzini JR, Franklin GF (1958) Sampled-data control systems. McGraw-Hill, New York

    MATH  Google Scholar 

  • Sivashankar N, Khargonekar PP (1994) Characterization and computation of the \(\mathcal{L}_{2}\)-induced norm of sampled-data systems. SIAM J Control Optim 32:1128–1150

    Article  MATH  MathSciNet  Google Scholar 

  • Tadmor G (1991) Optimal \(\mathcal{H}_{\infty }\) sampled-data control in continuous time systems. In: Proceedings of ACC’91, Boston, Massachusetts, pp 1658–1663

    Google Scholar 

  • Toivonen HT (1992) Sampled-data control of continuous-time systems with an \(\mathcal{H}_{\infty }\) optimality criterion. Automatica 28:45–54

    Article  MATH  MathSciNet  Google Scholar 

  • Yamamoto Y (1990) New approach to sampled-data systems: a function space method. In: Proceedings of 29th CDC, Honolulu, Hawaii, pp 1882–1887

    Google Scholar 

  • Yamamoto Y (1993) On the state space and frequency domain characterization of \({H}^{\infty }\)-norm of sampled-data systems. Syst Control Lett 21:163–172

    Article  MATH  Google Scholar 

  • Yamamoto Y (1994) A function space approach to sampled-data control systems and tracking problems. IEEE Trans Autom Control 39:703–712

    Article  MATH  Google Scholar 

  • Yamamoto Y (1999) Digital control. In: Webster JG (ed) Wiley encyclopedia of electrical and electronics engineering, vol 5. Wiley, New York, pp 445–457

    Google Scholar 

  • Yamamoto Y (2012) From vector spaces to function spaces—introduction to functional analysis with applications. SIAM, Philadelphia

    Book  MATH  Google Scholar 

  • Yamamoto Y, Khargonekar PP (1996) Frequency response of sampled-data systems. IEEE Trans Autom Control 41:166–176

    Article  MATH  MathSciNet  Google Scholar 

  • Yamamoto Y, Nagahara M, Khargonekar PP (2012) Signal reconstruction via \({H}^{\infty }\) sampled-data control theory—Beyond the Shannon paradigm. IEEE Trans Signal Process 60:613–625

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yutaka Yamamoto Ph.D, Professor .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag London

About this entry

Cite this entry

Yamamoto, Y. (2013). Optimal Sampled-Data Control. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_205-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_205-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, London

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Chapter history

  1. Latest

    Optimal Sampled-Data Control
    Published:
    14 November 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_205-2

  2. Original

    Optimal Sampled-Data Control
    Published:
    24 March 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_205-1