Fractional-order model reference adaptive controller design using a modified MIT rule and a feed-forward action for a DC-DC boost converter stabilization

Keziz, Bouziane; Djouambi, Abdelbaki; Ladaci, Samir

doi:10.1109/icee-b.2017.8192132

Cited by 6 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the specialized literature, there are many papers which present how the fractional order calculus can be used to control a dynamical system [1][2][3][4] (see the Model Reference Adaptive System (MRAS) [5][6][7][8][9][10][11]). Introducing the fractional order calculus in the adaptive control system leads to good performances.…”

Section: Introductionmentioning

confidence: 99%

Using the fractional order calculus in the combination of the MIT and Lyapunov stability method

Coman

Boldisor

2020

IRASE

View full text Add to dashboard Cite

The main idea of the current paper consists in introducing the fractional order calculus in a control system. To control the system, an adaptive control technique with reference model is used. The fractional order models for the plant and reference model are obtained. To achieve the performances imposed by the fractional order reference model, a fractional order adaptive control law is proposed, which is a combination of two methods (MIT and Lyapunov stability). The original contribution in this paper is the use of fractional order calculus in the combined MIT and Lyapunov stability method and showing the dynamic behavior of the system. Several simulations are used to emphasize the effectiveness and benefits of the proposed method.

show abstract

Section: Introductionmentioning

confidence: 99%

Using the fractional order calculus in the combination of the MIT and Lyapunov stability method

Coman

Boldisor

2020

IRASE

View full text Add to dashboard Cite

show abstract

“…Fractional order adaptive control is one of the most important emerging research topics in the present century [20][21] [22]. Among the proposed fractional adaptive control structures, MRAC-based approaches have attracted many researchers and designers because of its simplicity and efficiency [23]. However, when confronted to model uncertainties and disturbances, other control techniques have to be considered [24][25] [26].…”

mentioning

confidence: 99%

Robust Fuzzy Adaptive Control with MRAC Configuration for a Class of Fractional Order Uncertain Linear Systems

Bourouba

Ladaci

Illoul

2021

IJRCS

Self Cite

View full text Add to dashboard Cite

This paper investigates a novel robust fractional adaptive control design for a class of fractional-order uncertain linear systems. Based on the Model Reference Adaptive Control (MRAC) configuration, the objective of the proposed controller is to ensure the output of the controlled plant to track the output of a given reference model system, while maintaining the overall closed-loop stability despite external disturbances and model uncertainties. An adaptive fuzzy logic controller is employed to eliminate unknown dynamics and disturbance. Lyapunov stability analysis demonstrates and verifies the desired fractional adaptive control system stability and tracking performance. Numerical simulation results illustrate the efficiency of the proposed adaptive fuzzy control strategy to deal with uncertain and disturbed fractional-order linear systems.

show abstract

Model Reference Adaptive Fractional Order Controller Design

Singh

Deb

Agrawal

et al. 2020

Fractional Modeling and Controller Design of Robotic Manipulators

View full text Add to dashboard Cite

Fractional-order model reference adaptive controller design using a modified MIT rule and a feed-forward action for a DC-DC boost converter stabilization

Cited by 6 publications

References 18 publications

Using the fractional order calculus in the combination of the MIT and Lyapunov stability method

Using the fractional order calculus in the combination of the MIT and Lyapunov stability method

Robust Fuzzy Adaptive Control with MRAC Configuration for a Class of Fractional Order Uncertain Linear Systems

Model Reference Adaptive Fractional Order Controller Design

Contact Info

Product

Resources

About