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Artificial Neural Nets and Genetic Algorithms pp 575–578Cite as

Genetic Design of Robust PID Controllers

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Abstract

Genetic algorithms are proposed as a new and novel technique to solve the problem of designing a robust PID controller for a plant with model uncertainties. The evolutionary scheme used, involves generating two separate populations, one representing the controller and the other the plant. The controller population is then co-evolved against a fixed population of plants covering the plant uncertainty search space, such that the controller can control all the plants effectively. A time domain cost function subjected to a frequency domain vector margin stability constraint, is then deployed in order to obtain a robust controller design. This evolutionary approach is illustrated by evolving a PID controller for a linear plant which has a set of prescribed model uncertainties.

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Authors and Affiliations

  1. Intelligent Machinery Division, Research Institute for Design, Manufacturing, and Marketing University of Salford, Salford, M5 4WT, UK

    A. H. Jones & P. B. de Moura Oliveira

Authors
  1. A. H. Jones
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  2. P. B. de Moura Oliveira
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© 1998 Springer-Verlag Wien

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Jones, A.H., de Moura Oliveira, P.B. (1998). Genetic Design of Robust PID Controllers. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_127

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  • DOI: https://doi.org/10.1007/978-3-7091-6492-1_127

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83087-1

  • Online ISBN: 978-3-7091-6492-1

  • eBook Packages: Springer Book Archive

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