Adaptive Neural-Fuzzy Robust Position Control Scheme for Maglev Train Systems With Experimental Verification

Sun, Yougang; Xu, Junqi; Qiang, Haiyan; Lin, Guobin

doi:10.1109/tie.2019.2891409

Cited by 180 publications

(90 citation statements)

References 20 publications

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“…ANFIS architecture was first proposed by Jang [37] in 1993. This strategy is a widely applied artificial intelligent that combines the advantages of both ANN controller and fuzzy logic (FL) it is generally used for nonlinear and complex systems in various fields [38,39]. Garcia et al [40] designed an ANFIS based energy management system which consists of battery, renewable energy sources and hydrogen.…”

Section: Anfis-stsm Dpc Methodsmentioning

confidence: 99%

DPC Based on ANFIS Super-Twisting Sliding Mode Algorithm of a Doubly-Fed Induction Generator for Wind Energy System

Benbouhenni¹,

Boudjema²,

Belaïdi³

2020

JESA

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Conventional direct power control (DPC) using two hysteresis comparators and switching table for a doubly fed induction generator (DFIG) integrated in a wind turbine system (WTS) have some drawbacks such as harmonic distortion of voltages, reduced robustness and powers ripples. In order to resolve these problems, a super-twisting sliding mode control (STSMC) scheme based on adaptive-network-based fuzzy inference system (ANFIS) algorithm is employed. The validity of the employed approach was tested by using Matlab/Simulink software. Interesting simulation results were obtained and remarkable advantages of the proposed strategy were exposed including simple design of the control system, reduced powers ripples as well as the other advantages.

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Section: Anfis-stsm Dpc Methodsmentioning

confidence: 99%

DPC Based on ANFIS Super-Twisting Sliding Mode Algorithm of a Doubly-Fed Induction Generator for Wind Energy System

Benbouhenni¹,

Boudjema²,

Belaïdi³

2020

JESA

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“…For purpose of solving the coupling problems of velocity and pressure term, the governing equations and the boundary conditions of the 3D models are handled by semi-implicit method for pressure linked equation consistent (SIMPLEC) algorithm which is based on control volume method and presented by Van Doormaal and Raithby. [29][30][31] Also, the second-order upwind scheme is utilized to discretize the governing equations. The numerical solvers set in the commercial software FLUENT is utilized.…”

Section: Variables Rangementioning

confidence: 99%

Experimental test and numerical analysis for curvature ratios effect on the heat transfer and flow characteristics of a multi-layer winding hose

Qiang

et al. 2019

International Journal of Distributed Sensor Networks

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The effects of curvature ratios on heat transfer and flow characteristics based on multi-sensor technique for the multilayer winding hoses are studied. A multi-sensor-based experimental platform is established. The working fluid is oil and the multi-layer winding hoses are produced by winding a 13.00 mm diameter hydraulic hose on a reel from 1 to 12 turns. Experiments on different curvature ratios for the multi-layer winding hose with constant wall temperature are presented. A k-e standard model has been applied to present the simulations on heat transfer and turbulent flow. In order to solve this model, a finite volume method has been used. The simulation results are compared with the experimental results. The simulation results and experimental results are in the similar varying trends. The effects of centrifugal force in the multi-layer winding hose on heat transfer and pressure drop have been discussed.

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“…An adaptive neural-fuzzy sliding mode controller (AN-FSMC) is presented, which employs a sliding mode control, adaptive-fuzzy approximator, and the neural-fuzzy switching law. It reduces the impact of the disturbance and parameter perturbations with a smooth control current [3]. A radial basis function (RBF) neural network modeling approach is introduced for the compensation of the non-contact inductive gap sensor of the high-speed maglev train.…”

Section: Introductionmentioning

confidence: 99%

Disturbance Rejection Control Using a Novel Velocity Fusion Estimation Method for Levitation Control Systems

Xia

Dou

2020

IEEE Access

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Magnetic levitation has been applied to maglev trains and magnetic suspension wind tunnel. However, there are some problems with the existing levitation control. For example, it is difficult to extract smooth velocity signals from the gap sensor with noise. The classical differentiator is susceptible to noise, which makes the levitation system sometimes vibrate. The accuracy and stability of levitation control need to be improved. The velocity fusion estimation method (VFE) is proposed to extract the velocity signal from the gap and acceleration sensor, which is theoretically derived to prove that it reduced the noise of the velocity signal. Then disturbance rejection control(DRC) is proposed that add VFE into classical levitation control. Because of the high-quality velocity signal and accelerometer's fast responsiveness, it makes DRC have many advantages. The advantages of using the proposed control structure are that it improved the control accuracy of the target gap and resisted disturbance effectively. Air-gap fluctuations in levitation systems can be reduced in transient pulse disturbance test, white noise disturbance test, and external force disturbance test when it applies the proposed control method. The effectiveness and advantages of the proposed control method are verified by the simulation and experiments.

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Adaptive Neural-Fuzzy Robust Position Control Scheme for Maglev Train Systems With Experimental Verification

Cited by 180 publications

References 20 publications

DPC Based on ANFIS Super-Twisting Sliding Mode Algorithm of a Doubly-Fed Induction Generator for Wind Energy System

DPC Based on ANFIS Super-Twisting Sliding Mode Algorithm of a Doubly-Fed Induction Generator for Wind Energy System

Experimental test and numerical analysis for curvature ratios effect on the heat transfer and flow characteristics of a multi-layer winding hose

Disturbance Rejection Control Using a Novel Velocity Fusion Estimation Method for Levitation Control Systems

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