Abstract
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.
Highlights
The demand for a compact and convenient, environment-friendly, reduced maintenance of public transportation is rising [1]
We carry out simulation for the proposed adaptive control environment in the Magnetic Levitation Systems (MLS) (5) with matched (i.e., p2, p3 ) and mismatched (i.e., p1 ) parametric uncertainties using
Significant parameter variations result in performance degradation in MLS
Summary
The demand for a compact and convenient, environment-friendly, reduced maintenance of public transportation is rising [1]. The body position control in magnetic levitation systems takes place through an electromagnetic force [2]. The Magnetic Levitation (Maglev) based train is an efficient and frictionless transport system that fulfills such demands. Such systems have many outstanding attributes, like less noise, larger climbing slope ability, all-weather suitability, and longer life compared to a conventional wheel-rail transportation system [3]. Barring Maglev trains, the Magnetic Levitation Systems (MLS) find interest in many applications, like wind turbines, magnetic suspensions, space launching stations, Maglev fans, Maglev heart pumps, magnetic bearings, and many more [8,9]. 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
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