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Open AccessFeature PaperArticle

Generalization of the FOPDT Model for Identification and Control Purposes

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Department of Automatic Control, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj, Romania
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DySC Research Group on Dynamical Systems and Control, Department of Electromechanical, System and Metal Engineering, Ghent University, Tech Lane Science Park 125, B9052 Ghent, Belgium
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EEDT—Decisions and Control Core Lab Flanders Make, Tech Lane Science Park 131, B9052 Ghent, Belgium
*
Author to whom correspondence should be addressed.
Processes 2020, 8(6), 682; https://doi.org/10.3390/pr8060682
Received: 29 April 2020 / Revised: 24 May 2020 / Accepted: 5 June 2020 / Published: 10 June 2020
(This article belongs to the Section Computational Methods)
This paper proposes a theoretical framework for generalization of the well established first order plus dead time (FOPDT) model for linear systems. The FOPDT model has been broadly used in practice to capture essential dynamic response of real life processes for the purpose of control design systems. Recently, the model has been revisited towards a generalization of its orders, i.e., non-integer Laplace order and fractional order delay. This paper investigates the stability margins as they vary with each generalization step. The relevance of this generalization has great implications in both the identification of dynamic processes as well as in the controller parameter design of dynamic feedback closed loops. The discussion section addresses in detail each of this aspect and points the reader towards the potential unlocked by this contribution. View Full-Text
Keywords: first order plus dead time model; stability; gain margin; phase margin; fractional order system; frequency response; fractional order delay; fractional order control first order plus dead time model; stability; gain margin; phase margin; fractional order system; frequency response; fractional order delay; fractional order control
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Muresan, C.I.; Ionescu, C.M. Generalization of the FOPDT Model for Identification and Control Purposes. Processes 2020, 8, 682.

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