Non-linear robust control of a voltage-controlled magnetic levitation system with a feedback linearization approach

2011 ◽  
Vol 225 (1) ◽  
pp. 85-98 ◽  
Author(s):  
J Zhang ◽  
T Tao ◽  
X Mei ◽  
G Jiang ◽  
D Zhang
Keyword(s):  
Robust Control ◽  
Feedback Linearization ◽  
Magnetic Levitation ◽  
Levitation System ◽  
Non Linear ◽  
Magnetic Levitation System ◽  
Feedback Linearization Approach

Modelling, Simulation & Control of Non-Linear Magnetic Levitation System

2018 ◽  
Author(s):  
Muhammad Junaid Khan ◽  
Muhammad Junaid ◽  
Sahibzada Bilal ◽  
Sadia Jabeen Siddiqi ◽  
Haseeb Ahmad Khan
Keyword(s):  
Magnetic Levitation ◽  
Levitation System ◽  
Non Linear ◽  
Magnetic Levitation System ◽  
Simulation Control ◽  
Modelling Simulation

Observer-based feedback for the magnetic levitation system

2011 ◽  
Vol 34 (4) ◽  
pp. 422-435 ◽  
Author(s):  
Jerzy Baranowski ◽  
Paweł Piątek
Keyword(s):  
Magnetic Levitation ◽  
Numerical Differentiation ◽  
Careful Analysis ◽  
High Gain ◽  
Model Parameters ◽  
Stable Operation ◽  
Levitation System ◽  
Non Linear ◽  
Magnetic Levitation System ◽  
The Mathematical Model

Control of active magnetic bearings is an important area of research. The laboratory magnetic levitation system can be interpreted as a model of a single axis of bearings and is a useful testbed for control algorithms. The mathematical model of this system is highly non-linear and requires careful analysis and identification. The system is observable from position measurements as long as the electromagnet is powered as shown during the research. Practically measurable signals are the position and the coil current. The velocity that is necessary for any stabilizing control usually is obtained by numerical differentiation of the position. A more sophisticated approach is to estimate the velocity with an observer. Efficient observer types for this system are high-gain and non-linear reduced observers. The velocity estimated by an observer can be effectively used instead of a derivative in PID control of the position. Such an approach substantially improves control quality and extends the range of system’s stable operation. Even greater improvement is introduced by the addition of the non-linear feedforward to the control structure. The best results, provided the model parameters are correctly identified, are obtained with a control system consisting of the PID controller, the high-gain observer and the non-linear feedforward.

scholarly journals Robust Sliding Mode Control of a Magnetic Levitation System: Continuous-Time and Discrete-Time Approaches

2021 ◽  
Author(s):  
Pratik Vernekar ◽  
Vitthal Bandal
Keyword(s):  
Discrete Time ◽  
Feedback Linearization ◽  
State Feedback ◽  
Magnetic Levitation ◽  
Sliding Mode ◽  
Lyapunov Stability Theory ◽  
Mismatched Uncertainties ◽  
Levitation System ◽  
Full State Feedback ◽  
Magnetic Levitation System

This paper presents three types of sliding mode controllers for a magnetic levitation system. First, a proportional-integral sliding mode controller (PI-SMC) is designed using a new switching surface and a proportional plus power rate reaching law. The PI-SMC is more robust than a feedback linearization controller in the presence of mismatched uncertainties and outperforms the SMC schemes reported recently in the literature in terms of the convergence rate and settling time. Next, to reduce the chattering phenomenon in the PI-SMC, a state feedback-based discrete-time SMC algorithm is developed. However, the disturbance rejection ability is compromised to some extent. Furthermore, to improve the robustness without compromising the chattering reduction benefits of the discrete-time SMC, mismatched uncertainties like sensor noise and track input disturbance are incorporated in a robust discrete-time SMC design using multirate output feedback (MROF). With this technique, it is possible to realize the effect of a full-state feedback controller without incurring the complexity of a dynamic controller or an additional discrete-time observer. Also, the MROF-based discrete-time SMC strategy can stabilize the magnetic levitation system with excellent dynamic and steady-state performance with superior robustness in the presence of mismatched uncertainties. The stability of the closed-loop system under the proposed controllers is proved by using the Lyapunov stability theory. The simulation results and analytical comparisons demonstrate the effectiveness and robustness of the proposed control schemes.

scholarly journals Control PI difuso de un sistema de levitación magnética mediante un sistema embebido

2019 ◽  
Vol 20 (4) ◽  
pp. 1-11
Author(s):  
Yair Lozano Hernández ◽  
Oscar Octavio Gutiérrez Frías ◽  
Mario Villafuerte Bante
Keyword(s):  
Mathematical Model ◽  
Trajectory Tracking ◽  
Magnetic Levitation ◽  
Magnetic Bearing ◽  
Control Action ◽  
Tracking Tasks ◽  
Control Scheme ◽  
Levitation System ◽  
Non Linear ◽  
Magnetic Levitation System

In the present work, the design and implementation of a control scheme is presented. The aim of the control scheme is to perform regulation and trajectory tracking tasks in the position of a magnetic levitation system, which acts by electromagnetic repulsion. Such levitation system consists of a beam operated by an active magnetic bearing in pendular configuration. Although the Proportional Integral Derivative (PID) controller shows arithmetic simplicity, ease of use, high robustness and error equal to zero in stable state (Pal & Mudi, 2008), the magnetic levitation system mathematical model is highly non-linear and is subject to uncertainty or variation of its parameters. Therefore, the PID control does not guarantee the fulfillment of trajectory tracking tasks (Precup & Hellendoorn, 2011). In summary, a diffuse PI is used due to the system non-linear dynamics and the hysteresis present in the electromagnet. The controller design was made with the following methodology: the mathematical model and the non-linear characteristics of the system are analyzed; the universes of error discourse (derived from error and control action) are experimentally measured. The experimental data was used for the fuzzification, defuzzification, statement of the rules and controller gains. The implemented rules were designed for a PD-Fuzzy in which a numerical integration of the control action was applied, obtaining a Fuzzy PI. Finally, the implementation was made on the STM32F407G-DISC card, which was programmed with MATLAB-Simulink software tools. The experimental results show that the proposed controller works even below the horizontal, where the behavior can show singularities or physical problems such as magnetization. In compliance with the stated objectives for a range of -5 to 10 radians, these results are maintained even in the presence of disturbances, demonstrating the feasibility of the controller.

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