MAGLEV system modeling and LQR controller design in real time simulation

Maji, Debasis; Biswas, Mainak; Bhattacharya, Arghya; Sarkar, Gautam; Mondal, Tushar Kanti; Dey, Indranil

doi:10.1109/wispnet.2016.7566399

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…However, we can chart the relationship as a line in the 𝐾 𝐼 and 𝐾 𝐷 plane to determine the ranges of the 𝐾 𝐼 and 𝐾 𝐷 which guarantees the robust stability of the closed-loop system as shown in Figure 13(a). The preceding approaches should be applied to the remaining edge polynomial families 𝑝 (13) , 𝑝 (42) , and 𝑝 (43) where, Figure 13(b), Figure 13(c), and Figure 13(d) demonstrate regions of stability of the 𝑝 (13) , 𝑝 (42) and 𝑝 (43) respectively.…”

Section: 𝐺(𝑠mentioning

confidence: 99%

“…To address these challenges, two main approaches are commonly used for modeling: the linearized approach and the nonlinear approach. For linearized models, techniques such as PI, PID, fuzzy, and state feedback LQR are widely used as in [3,[12][13][14]. PID controller is one of the most common and straightforward control strategies used in various applications due to its simplicity and effectiveness.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: 𝐺(𝑠mentioning

confidence: 99%

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 linear system model and the nonlinear model are two well-known classification strategies for analysing systems that can be seen in the literature. For the linearized model: Proportional Integral control (PI), proportional-integral-derivative control (PID), Fuzzy logic controller, and linear-quadratic regulator (LQR) approaches are commonly applied as in [5][6][7][8]. According to [5], a magnetic levitation system (MLS) is a highly nonlinear open loop system which can be controlled by a proportional integral derivative (PID) controller with a derivative filter coefficient.…”

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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“…Since magnetic levitation systems possess intrinsically nonlinear dynamics and unstable structure, the modeling and control of these systems are tough issues. Thus, both linear and nonlinear techniques have been developed for various dynamics models [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Improvements of torque ripple reduction in DTC IM drive with arbitrary number of voltage intensities and automatic algorithm modification

Rosić¹,

Antić²,

Bebić³

2021

Turk J Elec Eng & Comp Sci

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Fractional order PI controllers based on two different analytical design methods are applied to a magnetic levitation system in this paper. The controller parameters are specified in order to fulfill specific frequency criteria. The first design method utilizes a unity feedback reference model whose forward path includes Bode's ideal loop transfer function. The second method uses the reference model that has been obtained via delayed Bode's ideal loop transfer function. The achievement of these two controllers are contrasted with each other on the magnetic levitation system using various criteria.

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MAGLEV system modeling and LQR controller design in real time simulation

Cited by 7 publications

References 4 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

Improvements of torque ripple reduction in DTC IM drive with arbitrary number of voltage intensities and automatic algorithm modification

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