scholarly journals Stabilization of the Magnetic Levitation System

2021 ◽  
Vol 11 (21) ◽  
pp. 10369
Author(s):  
Štefan Chamraz ◽  
Mikuláš Huba ◽  
Katarína Žáková

This paper contributes toward research on the control of the magnetic levitation plant, representing a typical nonlinear unstable system that can be controlled by various methods. This paper shows two various approaches to the solution of the controller design based on different closed loop requirements. Starting from a known unstable linear plant model—the first method is based on the two-step procedure. In the first step, the transfer function of the controlled system is modified to get a stable non-oscillatory system. In the next step, the required first-order dynamic is defined and a model-based PI controller is proposed. The closed loop time constant of this first-order model-based approach can then be used as a tuning parameter. The second set of methods is based on a simplified ultra-local linear approximation of the plant dynamics by the double-integrator plus dead-time (DIPDT) model. Similar to the first method, one possible solution is to stabilize the system by a PD controller combined with a low-pass filter. To eliminate the offset, the stabilized system is supplemented by a simple static feedforward, or by a controller proposed by means of an internal model control (IMC). Another possible approach is to apply for the DIPDT model directly a stabilizing PID controller. The considered solutions are compared to the magnetic levitation system, controlled via the MATLAB/Simulink environment. It is shown that, all three controllers, with integral action, yield much slower dynamics than the stabilizing PD control, which gives one motivation to look for alternative ways of steady-state error compensation, guaranteeing faster setpoint step responses.

2013 ◽  
Vol 341-342 ◽  
pp. 945-948 ◽  
Author(s):  
Wei Zhou ◽  
Bao Bin Liu

In view of parameter uncertainty in the magnetic levitation system, the adaptive controller design problem is investigated for the system. Nonlinear adaptive controller based on backstepping is proposed for the design of the actual system with parameter uncertainty. The controller can estimate the uncertainty parameter online so as to improve control accuracy. Theoretical analysis shows that the closed-loop system is stable regardless of parameter uncertainty. Simulation results demonstrate the effectiveness of the presented method.


2020 ◽  
Vol 42 (13) ◽  
pp. 2382-2395
Author(s):  
Armita Fatemimoghadam ◽  
Hamid Toshani ◽  
Mohammad Manthouri

In this paper, a novel approach is proposed for adjusting the position of a magnetic levitation system using projection recurrent neural network-based adaptive backstepping control (PRNN-ABC). The principles of designing magnetic levitation systems have widespread applications in the industry, including in the production of magnetic bearings and in maglev trains. Levitating a ball in space is carried out via the surrounding attracting or repelling magnetic forces. In such systems, the permissible range of the actuator is significant, especially in practical applications. In the proposed scheme, the procedure of designing the backstepping control laws based on the nonlinear state-space model is carried out first. Then, a constrained optimization problem is formed by defining a performance index and taking into account the control limits. To formulate the recurrent neural network (RNN), the optimization problem is first converted into a constrained quadratic programming (QP). Then, the dynamic model of the RNN is derived based on the Karush-Kuhn-Tucker (KKT) optimization conditions and the variational inequality theory. The convergence analysis of the neural network and the stability analysis of the closed-loop system are performed using the Lyapunov stability theory. The performance of the closed-loop system is assessed with respect to tracking error and control feasibility.


10.14311/482 ◽  
2003 ◽  
Vol 43 (5) ◽  
Author(s):  
T. Vyhlídal ◽  
P. Zítek

The features of internal model control (IMC) design based on the first order anisochronic model are investigated in this paper. The structure of the anisochronic model is chosen in order to fit both the dominant pole and the dominant zero of the system dynamics being approximated. Thanks to its fairly plain structure, the model is suitable for use in IMC design. However, use of the anisochronic model in IMC design may result in so-called neutral dynamics of the closed loop. This phenomenon is studied in this paper via analysing the spectra of the closed loop system.


2017 ◽  
Vol 58 ◽  
pp. 161-170 ◽  
Author(s):  
Georg Stettinger ◽  
Martin Benedikt ◽  
Martin Horn ◽  
Josef Zehetner ◽  
Clenn Giebenhain

2012 ◽  
Vol 462 ◽  
pp. 789-795
Author(s):  
Wei Tang ◽  
Xu Zhong Niu ◽  
Wen Juan Shan

It is very difficult to obtain perfect performance to apply the conventional PID (Proportional-Integral-Derivative) controller, because hydraulic headbox needs high precision total pressure control. Transfer function of total pressure control system was identified by using the direct identification method which is based on the least square method for the first-order plus delay time model. Then combined with IMC (Internal-Model-control) –PID method, an IMC-PID controller was designed, which is simple and only needed to adjust one parameter-the time constant of low pass filter. Acceptable performance can also be obtained by tuning time constant of the low pass filter when the model doesn't match with the real process. The algorithm was applied to total pressure control system of hydraulic headbox. Simulation and practical application show that, IMC-PID is of strong robustness and good dynamic characteristics. Finally, the control system is implemented by S7-300 PLC.


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