Design and Performance Analysis of Optimized Fractional Order PID Controller for Magnetic Levitation System

Dey, Soham; Banerjee, Subrata; Dey, Joykrishna

doi:10.1109/gucon50781.2021.9574026

Cited by 5 publications

(4 citation statements)

References 23 publications

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“…The chain movement can be achieved by using the average distance between two coots. The new position of the coot is calculated using equation (15).…”

Section: Chain Movementmentioning

confidence: 99%

“…If the coot got struck in the local optima, the random movement behaviour of the coot will help to escape and the new coot position will be calculated by using equation (13). Coot birds start to form a chain movement by taking the average position of two coots and updating their position by using the equation (15). The coot birds start to follow the leader based on equation ( 16) and the coot's leader updates their position based on equation (17).…”

Section: E Leading the Group By The Leaders Towards Optimal Areamentioning

confidence: 99%

“…Qui-Hua et al maglev system is used for measuring the densities of samples and also separating the poly methyl methacrylate particles [9]. In the year 2021, Soham Dey et al tuned the FOPID controller using the grey wolf algorithm and achieved the best transient and steadystate response [10]. Opposition-based Artificial Electric Field is used to tune [11] FOPID controller for an unstable magnetic ball suspension system, it achieved good performance criteria like peak overshoot, settling time, rise time, gain margin, and phase margin.…”

Section: Introductionmentioning

confidence: 99%

“…Debdoot Sain et al suggested an I-PD controller for the maglev system utilizing the Jaya algorithm in the same year 2018 and performed a robustness analysis [14]. In the year 2021, Soham Dey et al designed and analyzed the performance of the maglev system using the FOPID controller [15]. Yemei Qin et al developed a new control technique for a maglev system using a state-dependent ARX model [16].…”

Section: Introductionmentioning

confidence: 99%

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Design and Performance Analysis of a Nonlinear Magnetic Levitation System Using PID Controller Optimized With COOT Algorithm

Maheedhar,

Deepa

2023

IEEE Access

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Recent growth in magnetic levitation can be attributed to its ability to minimize friction and disturbance in industries, transportation, aerospace, biomedicine, and magnetic bearings. Due to the magnetic levitation system's nonlinear and unstable nature, control engineers found it exceedingly challenging to design a stabilizing controller. The magnetic levitation system is abbreviated as a maglev system. Using the integral square error criterion, a newly developed metaheuristic algorithm named the COOT algorithm is used to optimize the PID controller parameters. The performance of the proposed algorithm is evaluated using simulation and hardware with several kinds of reference trajectories and compared to the performance of other algorithms, such as the genetic algorithm and the whale optimization algorithm. Based on simulation and hardware results, it was determined that the proposed algorithm performed well with less settling time, rise time, and integral square error.

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“…The chain movement can be achieved by using the average distance between two coots. The new position of the coot is calculated using equation (15).…”

Section: Chain Movementmentioning

confidence: 99%