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Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain


Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

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Constrained Model Predictive Control for Linear Fractional-order Systems with Rational Approximation

Journal of Environmental Accounting and Management 8(1) (2019) 35--53 | DOI:10.5890/JAND.2019.03.004

Mandar M. Joshi$^{1}$, Vishwesh A. Vyawahare$^{2}$

$^{1}$ Electrical Engineering Department, Dar-al-Handasah, Pune, India

$^{2}$ Department of Electronics Engineering, Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, India

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This work deals with the design of model predictive control (MPC) strategy for linear fractional-order (FO) systems. Two FO systems with different characteristics, highly oscillatory response and nonminimum phase type, are considered to test the performance of the MPC design. Conventionally, a system with FO dynamics is represented using a finite memory integer-ordermodel. In order to evaluate the performance of MPC for such a situation, the integer-order rational approximation (Oustaloup’s recursive approximation) of the FO system is considered as the model, whereas the output of FO plant is calculated analytically by solving the linear FO differential equation at each sampling instant. The MPC methodology is applied in a constrained environment with limitations on the control input magnitude and its rate. The results confirm that designed MPC strategy works satisfactorily for the FO systems.


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