N. Kanagaraj^*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3213-3226, 2023, DOI:10.32604/iasc.2023.029901 - 17 August 2022

Abstract The design and analysis of a fractional order proportional integral derivate (FOPID) controller integrated with an adaptive neuro-fuzzy inference system (ANFIS) is proposed in this study. A first order plus delay time plant model has been used to validate the ANFIS combined FOPID control scheme. In the proposed adaptive control structure, the intelligent ANFIS was designed such that it will dynamically adjust the fractional order factors (λ and µ) of the FOPID (also known as PI^λD^µ) controller to achieve better control performance. When the plant experiences uncertainties like external load disturbances or sudden changes in the… More >

Hegazy Rezk^1,2,*, Mohammed Mazen Alhato³, Mohemmed Alhaider¹, Soufiene Bouallègue^3,4

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 185-199, 2021, DOI:10.32604/cmc.2021.016175 - 22 March 2021

Abstract In this research paper, an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator (DFIG) based wind energy system has been proposed. The proposed strategy used the robust Fractional-Order (FO) Proportional-Integral (PI) control technique. The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits. It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness. The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization (MRFO) More >

Aymen Rhouma^1,∗, Sami Hafsi^2,†, Faouzi Bouani³

Computer Systems Science and Engineering, Vol.34, No.5, pp. 305-313, 2019, DOI:10.32604/csse.2019.34.305

Abstract This paper provides an application of Fractional Model Predictive Control (FMPC) and fractional-order Proportional Integral controller (P I^λ) on a thermal system with time delay.The first controller is based on Grünwald-Letnikov’s method to predict the future dynamic behavior of the system. This method consists in replacing the non-integer derivation operator of the adopted system representation by a discrete approximation. Therefore, this controller is developed on the basis of a fractional order model. However, the second controller is founded on an extended version of Hermite-Biehler theorem to determine the complete set stabilizing P I^λ parameters Experiment results onto More >