Hybrid intelligent controller design for an unstable electromagnetic levitation system: a fuzzy interpolative controller approach

Gandhi, Ravi V.; Adhyaru, Dipak M.

doi:10.1504/ijaac.2019.102663

Cited by 10 publications

(2 citation statements)

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“…The Magnetic Levitation System (MLS) is one of the best practical applications to validate the effectiveness of control algorithms. MLS is a class of nonlinear, unstable, and electromagnetically coupled systems with a broad range of practical applications [37,38]. The schematic of voltage-controlled MLS is presented in Figure 1 [37].…”

Section: Practical Application and Resultsmentioning

confidence: 99%

Dual Extended State Observer Based Feedback Linearizing Control for Magnetic Levitation System with Mismatched Disturbances and Uncertainties

Gandhi¹,

Adhyaru²,

Bokoro³

2023

Preprint

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This research work presents the nonlinear control framework to estimate and reject the mismatched lumped disturbances acting on the nonlinear uncertain system. It is an unfortunate fact that the conventional Extended State Observer (ESO) is not capable to estimate the mismatched lumped disturbance and its derivative simultaneously for the systems. Also, the basic ESO is only suitable for systems with Integral Chain Form (ICF) structure. Similarly, the conventional Feedback Linearizing Control (FLC) approach is not robust for stabilizing the systems in the presence of disturbances and uncertainties. Hence, the nonlinear control framework is proposed to overcome the above issues which are composed of, (a) Dual Extended State Observer (DESO), and (b) DESO based FLC. The DESO provides information on the unmeasured state, mismatched disturbance, and its derivative. While the DESO-FLC utilizes the information from DESO to counter the effect of such disturbances and to stabilize the nonlinear systems around the reference point. The detailed closed-loop analysis is presented for the proposed control framework in the presence of lumped disturbances. The performance robustness of the presented design has been validated for the third order, nonlinear, unstable, and disturbed Magnetic Levitation System (MLS). The results of the DESO-FLC approach are compared with the most popular Linear Quadratic Regulator (LQR) and nonlinear FLC approaches based on the integral error criterion and the average electrical energy consumption.

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Section: Practical Application and Resultsmentioning

confidence: 99%

Dual Extended State Observer Based Feedback Linearizing Control for Magnetic Levitation System with Mismatched Disturbances and Uncertainties

Gandhi¹,

Adhyaru²,

Bokoro³

2023

Preprint

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show abstract

“…However, the usage of fixed operating conditions based on linear structure raises many questions over these controllers' applicability. The Structural modifications have been carried out to improve the performance, like fuzzy-PID [12], fractional PID [13], PSO-PID [14], and many more. With such modifications, the control problems, like stabilizing control and tracking control under regular load variations, get rectified for the MLS.…”

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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Control techniques for electromagnetic levitation system: a literature review

Pandey

Adhyaru

2022

Int. J. Dynam. Control

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Hybrid intelligent controller design for an unstable electromagnetic levitation system: a fuzzy interpolative controller approach

Cited by 10 publications

References 0 publications

Dual Extended State Observer Based Feedback Linearizing Control for Magnetic Levitation System with Mismatched Disturbances and Uncertainties

Dual Extended State Observer Based Feedback Linearizing Control for Magnetic Levitation System with Mismatched Disturbances and Uncertainties

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

Control techniques for electromagnetic levitation system: a literature review

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