Hybrid non-linear differentiator design for a permanent-electro magnetic suspension maglev system

Zhang, Lingling; Zhang, Zhizhou; Huang, Lihong

doi:10.1049/iet-spr.2011.0264

Cited by 7 publications

(10 citation statements)

References 17 publications

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“…In most of the MLS, the position (x) of moving object and current (i) passing from the coil are measurable variables. While the vertical velocity (dx/dt) of a moving object can be easily estimated using the available information of x and i using the reduced-order dynamics [22], or trackingdifferentiator [23]. In the past decade, the Disturbance Observer-Based Control (DOBC) methodologies have gained wide acceptance for estimating and rejecting the disturbances, uncertainties, unmodeled dynamics as a single lumped disturbance [24,25].…”

Section: Introductionmentioning

confidence: 99%

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

2021

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Maglev transportation system is become a hot topic for researchers because of the distinctive advantages, such as frictionless motion, low power consumption, less noise, and being environmentally friendly. The maglev transportation system’s performance gets sufficiently influenced by the control method and the magnetic levitation system’s dynamic performance, which is a critical component of the maglev transportation system. The Magnetic Levitation System (MLS) is a group of unstable, nonlinear, uncertain, and electromagnetically coupled practical application. Control objective of this study is to design a position stabilizing control strategy for Magnetic Levitation system under extreme uncertain parametric conditions using a reference model governed by a reference stabilizer and nonlinear adaptive control structure. After successful tuning the reference stabilizer with and without time-varying payload disturbance, the tracking-error dynamics are obtained in the presence of both matched and mismatched types of parametric uncertainties. Next, the close-loop stability theorem is formulated for Lyapunov stability analysis to get the design constraints, parameter update laws, and adaptive control law. Numerical simulations performed for a high range of parametric violations check the control design’s efficacy. The performance robustness gets confirmed by comparing the results with the nonlinear control approach. The MLS gets performance recovery and settles within safe limits in few seconds using the proposed methodology. However, the nonlinear controller faces permanent failure in stabilizing the MLS.

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Section: Introductionmentioning

confidence: 99%

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

2021

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“…Then, inspired by [16], a finite-time backstepping control strategy is established to fulfill the tracking control of the elevation and pitch angles. In addition, a HFTD [20] is introduced for approximating the intermediate control signal and its derivative to prevent the problem of complexity explosion in the traditional backstepping design protocol, and the error generated by the HFTD is weakened by the corresponding compensation signal. The main features of the presented control strategy are concluded as follows:…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Gradient Descent-Based Adaptive Neural Network Finite-Time Control Design for Attitude Tracking of a 3-DOF Helicopter

Wang¹

2021

Preprint

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This paper investigates a novel finite-time gradient descent-based adaptive neural network finite-time control strategy for the attitude tracking of a 3-DOF lab helicopter platform subject to composite disturbances. First, the radial basis function neural network (RBFNN) is applied to estimate lumped disturbances, where the weights, centers and widths of the RBFNN are trained online via finite-time gradient descent algorithm. Then, a finite-time backstepping control scheme is constructed to fulfill the tracking control of the elevation and pitch angles. In addition, a hybrid finite-time differentiator (HFTD) is introduced for approximating the intermediate control signal and its derivative to avoid the problem of "explosion of complexity" in the traditional backstepping design protocol. Moreover, the errors caused by the HFTD can be attenuated by the combination of compensation signals. With the aid of the stability theorem, it is proved that the closed-loop system is semi-globally uniformly ultimately boundedness in finite time. Finally, a comparison result is provided to illustrate the effectiveness and advantages of the designed control strategy.

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“…In his own article, he proposed three kinds of tracking differentiator, but the effect of tracking differential is not very good, and there is no good method for the problem of high order signal extraction. In recent years, many scholars have put forward a new tracking differentiator [9][10][11][12]. The Israeli scholar, Levent, proposed a high order sliding mode differentiator for the problem of high order differentiator [13].…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of a New Type of Tracking Differentiator

Li¹,

Kang²

2019

dtcse

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In this paper, a new tracking differentiator is proposed based on the inverse hyperbolic tangent function. Due to the complexity of the tracking differentiator and the inaccuracy of tracking accuracy, accurate differential signals cannot be obtained. It is globally asymptotically stable, and its singularities are stable nodes by proper selection of parameters. The inverse hyperbolic tangent acceleration function has strong nonlinear characteristics, simple structure, less parameters and convenient adjustment. The simulation results show that NTTD is not only simple in structure form and relatively less in design parameters, but also has some advantages in tracking precision, response time and filtering ability.

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Hybrid non-linear differentiator design for a permanent-electro magnetic suspension maglev system

Cited by 7 publications

References 17 publications

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

Finite-Time Gradient Descent-Based Adaptive Neural Network Finite-Time Control Design for Attitude Tracking of a 3-DOF Helicopter

Design and Analysis of a New Type of Tracking Differentiator

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