Volume no :24, Issue no: 1, November (2021)

Journal of Pure and Applied Mathematics: Advances and Applications

FRACTIONAL ORDER ADAPTIVE GENERALIZED PREDICTIVE CONTROL DESIGN BASED ON ROMERO GPC OPTIMIZATION CRITERION

Author's: Imen Deghboudj, Samir Ladaci and Khaled Belarbi
Pages: [1] - [20]
Received Date: April 18, 2021
Submitted by: Professor Jehad Alzabut
DOI: http://dx.doi.org/10.18642/jpamaa_7100122203

Abstract

In this paper, we propose a new fractional-order adaptive generalized predictive control (FA-GPC) design based on a fractional order Romero GPC cost function and online estimation of the plant model using the Recursive Least Square (RLS) algorithm. The plant model is supposed to be linear time-invariant with unknown parameters. The proposed controller is applied in numerical simulation to a DC motor system and compared with the classical adaptive generalized predictive control (A-GPC). Simulation results illustrate the effectiveness of the proposed adaptive FA-GPC controller.

Keywords

fractional order integral, fractional order adaptive control, generalized predictive control, Romero fractional cost function, DC motor.