On fractional predictive PID controller design method

Emmanuel Edet, Reza Katebi

Research output: Contribution to journalConference Contribution

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Abstract

A new method of designing fractional-order predictive PID controller with similar features to model based predictive controllers (MPC) is considered. A general state space model of plant is assumed to be available and the model is augmented for prediction of future output. Thereafter, a structured cost function is defined which retains the design objective of fractional-order predictive PI controller. The resultant controller retains inherent benefits of model-based predictive control but with better performance. Simulations results are presented to show improved benefits of the proposed design method over dynamic matrix control (DMC) algorithm. One major contribution is that the new controller structure, which is a fractional-order predictive PI controller, retains combined benefits of conventional predictive control algorithm and robust features of fractional-order PID controller.

Original languageEnglish
Pages (from-to)8555-8560
Number of pages6
JournalIFAC-PapersOnLine
Volume50
Issue number1
DOIs
Publication statusPublished - 18 Oct 2017
EventIFAC 2017 World Congress: The 20th World Congress of the International Federation of Automatic Control - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
https://www.ifac2017.org

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Controllers
Cost functions

Keywords

  • fractional-order PID controller
  • dynamic matrix control
  • model-based predictive controller

Cite this

Edet, Emmanuel ; Katebi, Reza. / On fractional predictive PID controller design method. In: IFAC-PapersOnLine. 2017 ; Vol. 50, No. 1. pp. 8555-8560.
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On fractional predictive PID controller design method. / Edet, Emmanuel; Katebi, Reza.

In: IFAC-PapersOnLine, Vol. 50, No. 1, 18.10.2017, p. 8555-8560.

Research output: Contribution to journalConference Contribution

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AB - A new method of designing fractional-order predictive PID controller with similar features to model based predictive controllers (MPC) is considered. A general state space model of plant is assumed to be available and the model is augmented for prediction of future output. Thereafter, a structured cost function is defined which retains the design objective of fractional-order predictive PI controller. The resultant controller retains inherent benefits of model-based predictive control but with better performance. Simulations results are presented to show improved benefits of the proposed design method over dynamic matrix control (DMC) algorithm. One major contribution is that the new controller structure, which is a fractional-order predictive PI controller, retains combined benefits of conventional predictive control algorithm and robust features of fractional-order PID controller.

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