Feedback linearization based optimal controller design for electromagnetic levitation system

Gandhi, Ravi V.; Adhyaru, Dipak M.

doi:10.1109/iccicct.2016.7987916

Cited by 15 publications

(3 citation statements)

References 15 publications

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“…The mismatched lumped disturbance for this experiment is the total effect due to the payload disturbance and the uncertain electromechanical parameters (i.e., ∆K m , ∆M b ). The voltage-controlled dynamics of MLS with mismatched lumped disturbance ( f (x, d, t)) is expressed by the following third-order nonlinear model [39]:…”

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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“…The figure clearly illustrates that the designed controller is robust enough to track the desired set point even when the mass of the ball has been changed to +25%. Likewise, the figure ( 29), (30), and (31) show the variation of the ball position with the actual mass of the ball and the +25% change in the mass of the ball for matched uncertainty with uncertainty in the coil resistance (R c ), sensing resistance (R s ), and unmatched uncertainty. The figure clearly illustrates that the designed controller is robust enough to track the desired set point even when the mass of the ball has been changed to +25%.…”

Section: Methodsmentioning

confidence: 99%

“…The optimal control has been designed using the Jaya algorithm to provide the required control action for the EML system [29]. [30] An optimal LQR based on feedback linearization is proposed to stabilize and track the reference input for the magnetic levitation system. Following a thorough examination of the literature on the various methods for controlling Maglev systems, several issues must be addressed in order to develop a more efficient controller for this system.…”

Section: Introductionmentioning

confidence: 99%

Robust-Optimal Control of Electromagnetic Levitation System with Matched and Unmatched Uncertainties: Experimental Validation

Pandey,

Adhyaru

2023

Preprint

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A robust-optimal control approach for an electromagnetic levitation system with matched and unmatched uncertainties is proposed in this article. Because of the uncertainties in the dynamics of an electromagnetic levitation system, it is necessary to design a robust control law that will ensure the stability of the system in the presence of these uncertainties. In this framework, the dynamics of an electromagnetic levitation system are addressed in terms of matched and unmatched uncertainties. The robust control problem is translated into the optimal control problem, where the uncertainties of the electromagnetic levitation system are reflected in the cost function. The optimal control method is used to solve the robust control problem. The solution to the optimal control problem for the electromagnetic levitation system is indeed a solution to the robust control problem of the electromagnetic levitation system under matched and unmatched uncertainties. The simulation and experimental results 1 demonstrate the performance of the designed control scheme. The performance indices such as IAE, ISE, ITAE, and ITSE are compared for both uncertainties to showcase the robustness of the designed control scheme.

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Design of Intelligent Stabilizing Controller and Payload Estimator for the Electromagnetic Levitation System: DOBFLC Approach

Gandhi

Adhyaru

2020

Soft Computing Applications

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Feedback linearization based optimal controller design for electromagnetic levitation system

Cited by 15 publications

References 15 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

Robust-Optimal Control of Electromagnetic Levitation System with Matched and Unmatched Uncertainties: Experimental Validation

Design of Intelligent Stabilizing Controller and Payload Estimator for the Electromagnetic Levitation System: DOBFLC Approach

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