Adaptive Cruise Control System for an Electric Vehicle Using a Fractional Order Model Reference Adaptive Strategy

Balaska, Hanane; Ladaci, Samir; Schulte, Horst; Djouambi, Abdelbaki

doi:10.1016/j.ifacol.2019.11.096

Cited by 17 publications

(10 citation statements)

References 13 publications

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“…By combining the fractional order model of (10) with the FGPC, we obtain the fractional orderMPC regulator represented in the following algorithm: Algorithm: FO-MPC: Specifications: parameters 𝑁 1 , P, M, Te, α, Q, R ,Wl, Wh and the value of Wc.…”

Section: Fractional Order Model Predictive Controlmentioning

confidence: 99%

“…Applications of FOC controllers are various with some realizations in research laboratories and real processes supervision like in robotic manipulators [6], [7], renewable energy systems [8], chaotic systems [9], vehicle control [10]. The concept of non-integer differentiation was developed far in the past and was recognized in the mathematics research community.…”

Section: Introductionmentioning

confidence: 99%

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Automatic voltage regulator performance enhancement using a fractional order model predictive controller

Deghboudj

Ladaci

2021

Bulletin EEI

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In this paper, a new design method for fractional order model predictive control (FO-MPC) is introduced. The proposed FO-MPC is synthesized for the class of linear time invariant system and applied for the control of an automatic voltage regulator (AVR). The main contribution is to use a fractional order system as prediction model, whereas the plant model is considered as an integer order one. The fractional order model is implemented using the singularity function approach. A comparative study is given with the classical MPC scheme. Numerical simulation results on the controlled AVR performances show the efficiency and the superiority of the fractional order MPC.

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Section: Fractional Order Model Predictive Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic voltage regulator performance enhancement using a fractional order model predictive controller

Deghboudj

Ladaci

2021

Bulletin EEI

Self Cite

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“…Proportional Integral(PI) and Proportional Integral Derivative (PID) controllers are the most commonly used controllers in the industry. Recently, a considerable amount of research has been done on fractional-order PI/PID controllers for various DC-DC converters, electrical drives, grid-connected and/or photovoltaic inverters, fractional controllers for multi-level converters in wind energy applications, microgrids, maximum power point tracking (MPPT) control of photovoltaic panels and in electric and hybrid vehicles [19]- [22]. More robust systems can be designed using fractional control with a remarkable improvement in the dynamic response compared to the conventional integer-order control.…”

Section: A Relevance Of Fractional Order Controlmentioning

confidence: 99%

“…The authors in [22] designed a fractional order model reference adaptive controller (FOMRAC) for cruise control of an EV. The power train with the motors, transmission system, controller, battery management system, power converters and cruise control system was modeled and simulated.…”

Section: ) Fractional-order Cruise Control Of Evmentioning

confidence: 99%

Fractional Order Control of Power Electronic Converters in Industrial Drives and Renewable Energy Systems: A Review

Warrier

Shah

2021

IEEE Access

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The power electronics industry is undergoing a revolution driven by an industry 4.0 perspective, with smart and green/hybrid energy management systems being the requirement of the future. There is a need to highlight the potential of fractional order control in power electronics for the highly efficient systems of tomorrow. This paper reviews the developments in fractional order control in power electronics ranging from stand-alone power converters, industrial drives and electric vehicles to renewable energy systems and management in smart grids and microgrids. Various controllers used in power electronics such as the fractional order PI/PID (FOPI/FOPID) and fractional-order sliding mode controllers have been discussed in detail. This review indicates that the plug-and-play type of intelligent fractional order systems needs to be developed for our sustainable future. The review also points out that there is tremendous scope for the design of modular fractional-order intelligent controllers. Such controllers can be embedded into power converters, resulting in smart power electronic systems that contribute to the faster and greener implementation of industry 4.0 standards. INDEX TERMS Fractional calculus, power electronic converters, fractional order control, industrial drives, electric vehicles, renewable energy applications, smart grids and microgrids, industry 4.0.

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“…Thanks to outstanding features of electric motors, EVs have opened various new research topics. Besides traditional but prospective studies on Power Electronics [3,4] and Electric Drives [5], there are many other subjects that are particularly oriented to EVs, for example, Motion Control [6], Energy Management System [7], and Autonomous Driving [8]. Motion control, also called an active safety system, has exploited the major advantages of electric motors installed on EVs very well.…”

Section: Introductionmentioning

confidence: 99%

Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles

Vo-Duy

Nguyễn

et al. 2020

Energies

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Electric vehicles are considered to be a greener and safer means of transport thanks to the distinguished advantages of electric motors. Studies on this object require experimental platforms for control validation purpose. Under the pressure of research, the development of these platforms must be reliable, safe, fast, and cost effective. To practically validate the control system, the controllers should be implemented in an on-board micro-controller platform; whereas, the vehicle model should be realized in a real-time emulator that behaves like the real vehicle. In this paper, we propose a signal hardware-in-the-loop simulation system for electric vehicles that are driven by four independent electric motors installed in wheels (in-wheel motor). The system is elaborately built on the basis of longitudinal, lateral, and yaw dynamics, as well as kinematic and position models, of which the characteristics are complete and comprehensive. The performance of the signal hardware-in-the-loop system is evaluated by various open-loop testing scenarios and by validation of a representative closed-loop optimal force distribution control. The proposed system can be applied for researches on active safety system of electric vehicles, including traction, braking control, force/torque distribution strategy, and electronic stability program.

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Adaptive Cruise Control System for an Electric Vehicle Using a Fractional Order Model Reference Adaptive Strategy

Cited by 17 publications

References 13 publications

Automatic voltage regulator performance enhancement using a fractional order model predictive controller

Automatic voltage regulator performance enhancement using a fractional order model predictive controller

Fractional Order Control of Power Electronic Converters in Industrial Drives and Renewable Energy Systems: A Review

Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles

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