Research on Control Strategy of Magnetic Levitation Gravity Compensator Based on Lyapunov Stability Criterion

Shi, Xiangyu; Mao, Qingqing

doi:10.1088/1757-899x/452/4/042146

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…Indeed, exact input-output feedback linearization and sliding mode control using Lyapunov functions are two promising methods for nonlinear control. [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Design a Robust Optimal Proportional-Integral-Derivative Controller for CE152 Magnetic Levitation System Using Bee Colony Algorithm

Al-Nahhal,

Almobaied

2024

PJBAS

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One of the most popular methods for giving feedback to the control loop in industrial control systems is the proportional-integral-derivative (PID) controller. The tuning of the PID controller, however, is currently being researched by engineers. In this research, a robust PID controller is proposed for the CE152 magnetic levitation system. Magnetic levitation, commonly referred to as maglev, is a technology that uses magnetic fields to levitate an object, such as a vehicle or train, above a track. By using magnetic forces to counteract gravitational and inertial forces, maglev systems can achieve frictionless movement and potentially higher speeds compared to conventional wheeled transportation. In this research, the robust PID controller is involved by computing all stabilized PID controller gains for the affine linear characteristic polynomial in the presence of uncertain parameters using the parameter space approach and the edge theorem. The results of the parameter space approach are ranges of PID gains (𝐾 𝑃 , 𝐾 𝐷 , 𝐾 𝐼 ). Here, the optimal PID gains were chosen by the Artificial Bee Colony optimization algorithm to get optimal performance for CE152 magnetic levitation. The research defines a specific performance index function that quantifies the system's time-domain step response criteria (small overshoot percentage with significant minimization of both settling and rising times). This index function is inversely proportional to the desired performance criteria, aiming to optimize the system's performance. MATLAB simulations are used to validate and demonstrate the efficiency of the proposed graphical method for enhancing stability in the maglev system.

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“…Indeed, exact input-output feedback linearization and sliding mode control using Lyapunov functions are two promising methods for nonlinear control. [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Design a Robust Optimal Proportional-Integral-Derivative Controller for CE152 Magnetic Levitation System Using Bee Colony Algorithm

Al-Nahhal,

Almobaied

2024

PJBAS

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“…The graphic PID development methodology for the maglev system was published in [9], which used the D-partition approach in the design of controller. Sliding mode control, Lyapunov functions, and output feedback control are a promising techniques for nonlinear viewpoints [10][11][12]. Although PID is the easiest and most inexpensive of these controllers in develop and implement, the major drawback of PID controller is a tuning of PID gains (KP, KI, and KD).…”

Section: Introductionmentioning

confidence: 99%

Robust-PID controller design for magnetic levitation system using parameter space approach

Almobaied¹,

Al-Nahhal²,

Issa³

2023

World J. Adv. Eng. Technol. Sci.

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Recently, implementation of air magnetic suspension systems has become more challenging due to the growing demand for lightweight technologies, comfortable cabins, vehicle safety stability, and pollution control. Magnetic levitation, or Maglev, is the method of propelling a target into the air by adjusting different magnetic forces. The absence of contact and the avoidance of wear and friction phenomena are key considerations in the applications of magnetic levitation technology. Due to the high nonlinearity in the modelling process of such kind of systems, the stabilizing of magnetic levitation has been considered as a challenging task for many researchers in control engineering sector. The computation of all stabilizing PID gains controllers for the magnetic levitation benchmark ED-4810 (Maglev) is demonstrated in this paper using two different scenarios. In the first one, the tuning parameters of the classical PID controller (KP, KI, and KD) are assumed to be the uncertain parameters. The second scenario demonstrates the uncertainty in the transfer function of the system by using the resistance and the inductance as uncertain parameters. The characteristic polynomial of the linearized uncertain model is shown to be an unstable affine polynomial using the Zero Exclusion Theorem and the singular frequencies technique. The parameter space approach is used to illustrate the values of all PID parameters in order to achieve robust stability in the two scenarios. The effectiveness of the presented graphical technique has been verified through MATLAB simulation to obtain robust stability for magnetic levitation systems.

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Computation Of Stabilizing PID Controllers For Magnetic Levitation System With Parametric Uncertainties

Almobaied

Al-Nahhal

Issa

2021

2021 International Conference on Electric Power Engineering – Palestine (ICEPE- P)

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Research on Control Strategy of Magnetic Levitation Gravity Compensator Based on Lyapunov Stability Criterion

Cited by 3 publications

References 8 publications

Design a Robust Optimal Proportional-Integral-Derivative Controller for CE152 Magnetic Levitation System Using Bee Colony Algorithm

Design a Robust Optimal Proportional-Integral-Derivative Controller for CE152 Magnetic Levitation System Using Bee Colony Algorithm

Robust-PID controller design for magnetic levitation system using parameter space approach

Computation Of Stabilizing PID Controllers For Magnetic Levitation System With Parametric Uncertainties

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