Fractional order PID sliding mode control for speed regulation of permanent magnet synchronous motor

Zaihidee, Fardila Mohd; Mekhilef, Saad; Mubin, Marizan

doi:10.36909/jer.v9i3a.9209

Cited by 4 publications

(3 citation statements)

References 28 publications

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“…GA is a subdivision of adaptive algorithms. Nonlinear dynamical systems, robotics, planning techniques, and data analysis are just a few more real-world uses for GA [8]. To promote the widespread adoption of PMSM for Vehicle it is imperative to provide a robust propulsion system.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Modeling and Analysis Adaptive-Fuzzy FOPID System With Genetic Algorithm Tuned FOPID Speed Control Of PMSM For Electric Vehicle System

sime,

Aluvada,

Tolosa

et al. 2024

Preprint

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This study is based on the speed control performances of a Synchronous Motor with a Permanent Magnetic electric vehicle drive system. Due to the fast depletion of fossil resources, pollution, and issues with the global environment caused by internal combustion vehicles, it must change to a renewable energy source. Offering advantages, including high dependability, compact volume, lightweight construction, and high efficiency, PMSM is being used in EV drive systems, including high dependability, compact volume, lightweight construction, and high efficiency.PMSM is being used in EV drive systems. This kind of motor drive is among the best options for robotics and machine vision applications that require intensive motion control. Additionally, it is being researched for high-power uses including industrial drives and vehicle propulsion. The parameter FOPID controller was generally tuned by GA using an integral square Error criterion, which realizes a good dynamic behavior of the system. While maintaining good dynamic performance, a precise speed and current tracking ensure stability tolerance against parameter fluctuations and rapid load disturbance. The AFFOPID's speed response demonstrates that it outperforms FOPID and PID controllers with respect to dynamic performance.AFFOPID has less overshoot (0.03645%), rise time(0.016)and settling time (0.001495seconds)than FOPID, which has overshoot(11.798%), rise time(0.01408), and settling time(0.015335).and PID that overshoot by21.341%, rising time that was 0.014208 seconds, and settling time that was 0.01495 seconds.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Modeling and Analysis Adaptive-Fuzzy FOPID System With Genetic Algorithm Tuned FOPID Speed Control Of PMSM For Electric Vehicle System

sime,

Aluvada,

Tolosa

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…25,26 Besides, in terms of enhancing SMCs' transient response, a number of controllers were developed, including the integral sliding mode controller (ISMC) 27 as well as the proportional-integral-derivative (PID)-based sliding mode controller (PID-SMC). 28 One particular improvement which, in addition to achieving fast transient response, was also able to maintain finite-time convergence, is a combination between the ISMC and TSMC designs, namely, the integral terminal sliding mode controller (ITSMC). 29 Nevertheless, the interdependency between all introduced approaches, which potentially worsens their limitations so to speak, is still considered a major issue.…”

Section: Introductionmentioning

confidence: 99%

Skill learning approach based on impedance control for spine surgical training simulators with haptic playback

Brahmi

Bojairami

Ghomam

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, a robust adaptive impedance control based on the modified function approximation technique, and augmented with a novel integral nonsingular terminal sliding mode control, is proposed for a surgical haptic system. The haptic device is maneuvered by surgeons, whereby the mode of action, motion path, and haptic dynamics are rendered as unknowns. The inclusion of integral nonsingular terminal sliding mode control leverages the capability of ensuring consistent tracking of system’s trajectories performance, fast transient response, finite-time convergence, improved robustness, and reduced chattering. However, the modified function approximation technique strategy allows to estimate model’s dynamics regardless of the availability of dynamic uncertainties’ lower and upper bounds. In addition, an estimate of the intended motion mode and path is integrated in the evolved adaptive impedance control, via radial basis function neural network, permitting the haptic arm to track the target impedance model. Finally, using the haptic arm, controlled experimental cases and comparative study were done, after which the proposed surgical simulator adopted the results for real-time validation.

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“…The general form of the FOPID is PI λ D μ . Fractional calculus based conventional PID controller is further expanded into PI λ D μ (Tajbakhsh et al,2014, Narmada et al,2014, Mohammed et al,2018, Can et al,2021& Zaihidee et al,2021. The transfer function in case of a conventional PID controller would be…”

Section: Motor Modelmentioning

confidence: 99%

Ant Colony Optimization based Optimal Tuning of Fractional Order (FO) PID Controller for controlling the Speed of a DC Motor

Gupta

Kaur

Gupta

2022

JER is an international, peer-reviewed journal that publishes f

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This paper deals with the use of a FOPID Controller for the direct current motor speed controlling process. FOPID Controller consists of fractional integral-derivative terms along with the integer order proportional terms. It is a specific controller in which orders of derivative and integral lie in between fractions of 0 and 1. Mathematical model of DC motor and controller is presented whose field has been excited by an external source. In this paper, the simulation part of a DC motor for controlling its speed using a FOPID Controller has been performed. There are five degrees of freedom in FOPID controller contrary to traditional PID controller which have only three. The values of the five parameters (Kp, Ki, Kd, λ, μ) of a FOPID Controller have been improved by reducing the ITAE (Integral Time Absolute Error) cost to best possible value using the ACO i.e. Ant Colony Optimization Technique. The closed loop ZNT (Ziegler-Nichols Tuning) method used for the tuning of DC motor. Simulink model of proposed system has been developed and simulated to find out the minimum cost. The intensification in the steady and transient behaviors of the system. The results also exhibit significant improvement in the rise time, settling time and peak overshoot as compared to the other optimization methods.

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Fractional order PID sliding mode control for speed regulation of permanent magnet synchronous motor

Cited by 4 publications

References 28 publications

RETRACTED: Modeling and Analysis Adaptive-Fuzzy FOPID System With Genetic Algorithm Tuned FOPID Speed Control Of PMSM For Electric Vehicle System

RETRACTED: Modeling and Analysis Adaptive-Fuzzy FOPID System With Genetic Algorithm Tuned FOPID Speed Control Of PMSM For Electric Vehicle System

Skill learning approach based on impedance control for spine surgical training simulators with haptic playback

Ant Colony Optimization based Optimal Tuning of Fractional Order (FO) PID Controller for controlling the Speed of a DC Motor

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