Fuzzy logic control of electrodynamic levitation devices coupled to dynamic finite volume method analysis

Mabrouk, Abd Elhamid; Cheriet, Ahmed; Féliachi, Mouloud

doi:10.1016/j.apm.2012.11.025

Cited by 8 publications

(5 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Computation of magnetic field, eddy current and developed forces of an electrodynamic levitation device by finite volume method modelling caused reduction of storage memory and computation time [2]. Lift and thrust or braking forces in translating and rotating electodynamic wheels are modeled by 2D steady state FEM [3].…”

Section: Introductionmentioning

confidence: 99%

Modelling and Analysis of Permanent Magnet Electrodynamic Suspension Systems

Rezaei¹,

Vaez‐Zadeh²

2014

PIER M

View full text Add to dashboard Cite

Abstract-In this paper, an analytical model of permanent magnet electrodynamic suspension systems (PEDSs) is proposed. Horizontal and vertical magnetic fields of a permanent magnet (PM) are effectively approximated by sinusoidal functions. By this means, closed form solutions are obtained for lift and drag forces of PEDSs for the first time. The suspension system is then modelled by finite element method (FEM). The accuracy of the analytical model is validated by FEM and experimental measurements.

show abstract

Section: Introductionmentioning

confidence: 99%

Modelling and Analysis of Permanent Magnet Electrodynamic Suspension Systems

Rezaei¹,

Vaez‐Zadeh²

2014

PIER M

View full text Add to dashboard Cite

show abstract

“…The knowledge base comprises a database that provides necessary definitions to ensure a proper functioning of the controller and a rule base that contains a set of fuzzy control rules [21]. A fuzzy control rule provides a convenient way to represent control goals and policies of field experts and has the following form:

\begin{matrix} R^{j} : If x_{1} is A_{1}^{j} and \dots and x_{n} is A_{n}^{j} then u_{f l} is B^{j}, \\ j = 1,2, \dots, M, \end{matrix}

where x i and u fl are linguistic variables representing i th input of the controller and fuzzy logic control input, respectively, A i j and B j are linguistic values of the linguistic variables x i and u fl , respectively, and M is the number of fuzzy control rules.…”

Section: Preliminariesmentioning

confidence: 99%

Robust Fuzzy Logic Stabilization with Disturbance Elimination

Danapalasingam

2014

The Scientific World Journal

View full text Add to dashboard Cite

A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design.

show abstract

“…During the past few years, the finite volume method (FVM) has demonstrated its efficiency and accuracy in the solution of different kinds of electromagnetic problems such as magnetostatic, eddy current and magnetic force computation (Mabrouk et al ., 2013a, 2013b; Yaoqin et al ., 2001; Li et al ., 2012; Zou et al ., 2004). Compared to the finite element method (FEM), the FVM ensures both robustness of computation and facilities of implementation.…”

Section: Introductionmentioning

confidence: 99%

“…The FVM coupled with the nonconforming mesh (NC-FVM) has already been developed by Mabrouk et al . (2013a, 2013b) and Cheriet et al .…”

Section: Introductionmentioning

confidence: 99%

Arbitrary movement simulation using 3D NC-FVM for electromagnetic problems

Amrani

Cheriet

Féliachi

2018

COMPEL

Self Cite

View full text Add to dashboard Cite

Purpose The purpose of this paper is to propose to simulate an arbitrary movement in electromagnetic problems by means of a 3D nonconforming finite volume method (NC-FVM). The moving part can be displaced according to the x, y and/or z direction. Design/methodology/approach The 3D nonconforming mesh technique coupled to the FVM is used to handle arbitrary displacement of moving parts. Accordingly, the whole problem domain is divided into two parts: moving part and fixed part. Both parts are meshed independently. By using a suitable connection between both fixed and moved meshes, the movement can be performed according to the three axes. Findings The TEAM Workshop Problem No. 23 is used to test the proposed method. The calculated values of the magnetic force applied to the permanent magnet for different positions of the magnet show the efficiency of the proposed method. Originality/value This paper introduces the NC-FVM to solve electromagnetic problems which contain moving parts. Here, the movement can be performed according to the three axes.

show abstract

Fuzzy logic control of electrodynamic levitation devices coupled to dynamic finite volume method analysis

Cited by 8 publications

References 14 publications

Modelling and Analysis of Permanent Magnet Electrodynamic Suspension Systems

Modelling and Analysis of Permanent Magnet Electrodynamic Suspension Systems

Robust Fuzzy Logic Stabilization with Disturbance Elimination

Arbitrary movement simulation using 3D NC-FVM for electromagnetic problems

Contact Info

Product

Resources

About