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Encyclopedia of Systems and Control pp 1–8Cite as

Control System Optimization Methods in the Frequency Domain

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Abstract

When designing a compensator, there are typically a range of solutions that provide a closed-loop response meeting the design requirements. An optimal solution is one that meets the design specifications while minimizing or maximizing an objective function. The process for formulating control compensator design as an optimization problem is described in this article. An example case is given to illustrate control system optimization methods in the frequency domain.

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Bibliography

  • Franklin GF, Powell JD, Emami-Naeini A (2019) Feedback control of dynamic systems, 8th edn. Pearson, Upper Saddle River

    MATH  Google Scholar 

  • Tischler MB, Berger T, Ivler CM, Mansur, HM, Soong, J (2017) Practical methods for aircraft and rotorcraft flight control design using multi-objective parameter optimization. AIAA education series. Reston, VA

    Book  Google Scholar 

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Author information

Authors and Affiliations

  1. Shiley School of Engineering, University of Portland, Portland, OR, USA

    Christina M. Ivler

Authors
  1. Christina M. Ivler
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Corresponding author

Correspondence to Christina M. Ivler .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Aero/Astro Dept, Stanford University, Stanford, CA, USA

    J. David Powell

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Ivler, C.M. (2019). Control System Optimization Methods in the Frequency Domain. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_100163-1

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_100163-1

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

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

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