Performance enhancement of magnetic levitation system using teaching learning based optimization

Yadav, Shekhar; Verma, Santosh Kumar; Nagar, Shyam Krishna

doi:10.1016/j.aej.2017.08.016

Cited by 32 publications

(16 citation statements)

References 10 publications

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“…PID controller is known as the proportional, integral and derivative controller. The popularity of PID is very high in control system society because it has special characteristics such as controlling capability [11]. It is commonly considered as an extreme form of a phase lead-lag compensator.…”

Section: Pid Controllermentioning

confidence: 99%

“…Apart from PID controller, several researchers have been used Fuzzy logic control with PID control or other controller alone. Shekhar Yadav [11] used Teaching Learning Based Optimization (TLBO) to optimize the parameter of the PID controller and compared the performance with the conventional control techniques. Tania Tariq Salim [12] presented a fuzzy logic controller design of linear magnetic levitation system and compared the performance of fuzzy logic control and Linear Quadratic Regulator Controller (LQRC) for the same system's model.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Control of a Magnetic Levitation System Using an Analog Controller

Rasid¹,

Hossain²,

Hoque³

et al. 2019

Acta electron. Malays.

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This paper presents the modeling and control the position of the ferromagnetic ball in a controlled environment using analog controller where the current is varied in the electromagnet to keep the stable position of the ball. Generally, open loop magnetic levitation system is unstable non-linear system. Also, external disturbances are acting on the system making the control is very complex. First, analog controller based magnetic suspension system model is built to represent the dynamic behavior between the current of the electromagnetic coil and position of the ferromagnetic ball suspended. The model is developed using PID controller because it is the most popular industrial controller today. The PID controller is designed using pole assigned method so that pole of the designed system lies on the left half plane. The developed model is simulated using the proposed analog PID controller where step response and frequency response of the system is measured and made the system stable by tuning the proportional, integral and derivative parameter of the PID control. Then, experimental setup of the magnetic levitation system is developed and same control methodology is used to stable the position of the ferromagnetic ball as with simulation. Finally, the position of the levitated ball is suspended using the same control parameter of simulation.

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Section: Pid Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Control of a Magnetic Levitation System Using an Analog Controller

Rasid¹,

Hossain²,

Hoque³

et al. 2019

Acta electron. Malays.

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show abstract

“…To overcome those difficulties in designing a controller for position control of the levitated object in a MAGLEV system, variety of techniques have been developed by different researchers. Naturally, by optimizing their parameters utilizing various approaches, PID controllers has been used in controlling MAGLEV systems as well [20][21][22][23][24][25][26][27]. Several researchers have developed different FOPID controllers to obtain stable levitating and reinforced trajectory tracking control of Maglev system [28][29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Design of a MAGLEV System with PID Based Fuzzy Control Using CS Algorithm

Ataşlar-Ayyıldız

Karahan

2020

Cybernetics and Information Technologies

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The main aim of this study consists of proposing a simple but effective and robust approach for PID type fuzzy controller (Fuzzy-PID) in order to improve the dynamics and stability of a magnetic ball levitation system. The design parameters of the proposed controller are optimally determined based on Cuckoo Search (CS) algorithm. During the optimization, a time domain objective function is used for minimizing the values of common step response characteristics for the optimal selection of the controller parameters. Robustness tests are performed to evaluate the performance of the proposed controller through extensive simulations under load disturbance, parametric variation and changes in references. Moreover, to show the advantage and compare the performance of the proposed controller, the PID and Fractional Order PID (FOPID) controllers tuned with CS are designed. The simulation results and comparisons with the CS based PID and FOPID controllers demonstrate that the CS based Fuzzy-PID controller has superior performance depending on small overshoot, short settling time, fast rise time and minimum steady state error. Compared with the PID and FOPID controller tuned with CS, the simulation results show that the proposed Fuzzy-PID controller tuned with CS outperforms in terms of the accuracy, robustness and the least control effort.

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“…In order to obtain better control effects, the control algorithms are becoming more and more complicated. In [1], [2], the parameters of the PID controller are optimized by the grey wolf optimizer and teaching learning based optimization.…”

Section: Introductionmentioning

confidence: 99%

Design and Real-Time Implementation of Takagi–Sugeno Fuzzy Controller for Magnetic Levitation Ball System

2020

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An integral state feedback control method based on T-S fuzzy model is proposed for nonlinear and unstable magnetic levitation ball system in this paper. Firstly, the fuzzy model of the magnetic levitation ball is derived from the nonlinear dynamic model by using the sector nonlinearity, and the local controller is designed by using the integral state feedback control. The global controller is constructed by a parallel distributed compensation (PDC) method, and the feedback gain is obtained using a linear matrix inequality (LMI). Finally, the integrated state feedback controller is applied to the position control of the magnetic levitation ball system, and a dSPACE real-time control platform is established for experimental research. The simulation and experiment are performed to prove that the designed controller can levitate the ball stably, and has better control performance. INDEX TERMS Magnetic levitation ball system, T-S fuzzy model, integral state feedback, parallel distributed compensation (PDC), linear matrix inequality (LMI), dSPACE.

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Performance enhancement of magnetic levitation system using teaching learning based optimization

Cited by 32 publications

References 10 publications

Modeling and Control of a Magnetic Levitation System Using an Analog Controller

Modeling and Control of a Magnetic Levitation System Using an Analog Controller

Design of a MAGLEV System with PID Based Fuzzy Control Using CS Algorithm

Design and Real-Time Implementation of Takagi–Sugeno Fuzzy Controller for Magnetic Levitation Ball System

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