PID, fuzzy and LQR controllers for magnetic levitation system

Unni, Arjun C.; Junghare, Anjali S.; Mohan, Vivek; Ongsakul, Weerakorn

doi:10.1109/cogen.2016.7728977

Cited by 22 publications

(14 citation statements)

References 6 publications

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“…This control system is working based on the calculations of the error value, trying to reduce the error percentage by adjusting the controller parameters. The general form of this controller is formulated as below [20].…”

Section: Pid Controllermentioning

confidence: 99%

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A New Planar Electromagnetic Levitation System Improvement Method Based on Simlab Platform in Real Time Operation

Yaseen¹,

Haider²

2017

PIER M

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Abstract-Electromagnetic levitation system is commonly used in the field of magnetic levitation system train. Magnetic levitation technology is one of the most promised issue of transportation and precision engineering. Magnetic levitation systems are free of problems caused by friction, wear, sealing and lubrication. In this paper, a new prototype of the magnetic levitation system is proposed, designed and successfully tested via SIMLAB platform in real time. In addition, the proposed system was implemented with an efficient controller, which is linear-quadratic regulator (LQR) and compared with a classical controller which is proportional-integral-derivative (PID). The present system has been tested with two different criteria: signal test and load test under different input signals which are Sine wave and Squar wave. The findings prove that the suggested levitation system reveals a better performance than conventional one. Moreover, the LQR controller produced a great stability and optimal response compared to PID controller used at same system parameters.

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Section: Pid Controllermentioning

confidence: 99%

“…The Linear Quadratic Regulator (LQR) method is similar to Root Locus approach by inserting the closed loop poles of the system into the desired location [20]. The EMS linearization dynamic model is formulated by state space as below: …”

Section: Linear Quadratic Regulator (Lqr) Controllermentioning

confidence: 99%

A New Planar Electromagnetic Levitation System Improvement Method Based on Simlab Platform in Real Time Operation

Yaseen¹,

Haider²

2017

PIER M

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show abstract

“…The results show the high speed response for the control system compared with a given reference; also the simulation observes the robustness due to disturbance [8]. Unni et al (2016) design a PID, FUZZY and LQR control system. The systems implemented in real time using MATLAB software.…”

Section: Introductionmentioning

confidence: 99%

“…The researchers compare the control system operations based on peak overshoot, rise time and settling time. The researchers recorded the features of each operation case [9]. Zhu et al (2017) developed a six degree of freedom (6 DOF) magnetic levitation system.…”

Section: Introductionmentioning

confidence: 99%

Modelling Planar Electromagnetic Levitation System based on Phase Lead Compensation Control

Yaseen¹

2017

ijacsa

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Abstract-Electromagnetic Levitation System is commonly used in the field of train Maglev (magnetic levitation) system. Modelling Maglev system including all the magnetic force characteristics based on the current and position. This paper presents 2DOF model which represents a sample of uniform rigid plane body based on the functions of current and the air gap. The present work identifies the dynamic correlation of the levitation system of the Maglev using three sub-models. Lead controller is developed to achieve system stability by considering the system correlation of system moments and inductance variations. The control properties of the present model are obtained through SIMLAB microcontroller board to achieve the stable Maglev system.

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“…There are some studies about type-1 fuzzy control of magnetic levitation in [34][35][36]. In [37] robust adaptive inverse control of a class of nonlinear systems with prandtl-ishlinskii hysteresis model has been presented.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Intelligent Inverse Control Of Nonlinear Systems With Regard To Sensor Noise And Parameter Uncertainty (Magnetic Ball Levitation System Case Study)

Asad

Shamsi

Ivani

et al. 2016

International Journal on Smart Sensing and Intelligent Systems

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PID, fuzzy and LQR controllers for magnetic levitation system

Cited by 22 publications

References 6 publications

A New Planar Electromagnetic Levitation System Improvement Method Based on Simlab Platform in Real Time Operation

A New Planar Electromagnetic Levitation System Improvement Method Based on Simlab Platform in Real Time Operation

Modelling Planar Electromagnetic Levitation System based on Phase Lead Compensation Control

Adaptive Intelligent Inverse Control Of Nonlinear Systems With Regard To Sensor Noise And Parameter Uncertainty (Magnetic Ball Levitation System Case Study)

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