IMPLEMENTATION OF CONTROL ALGORITHMS IN BALL MAGNETIC LEVITATION SYSTEM TO IMPROVE SYSTEM PARAMETERS

Magnetic Levitation System (Maglev) is an approach which is currently widely applied in different areas like semiconductor, transportation, power generation, household appliances and etc. Since Magnetic Levitation System is a highly non-linear system, constructing a successful controller which has robust performance becomes a big challenge. The most conventional method of building Maglev is PID controller. However findings of controller’s parameters which ar

Synthesis of Hybrid Fuzzy Logic Law for Stable Control of Magnetic Levitation System

In this paper, we present a method to design a hybrid fuzzy logic controller (FLC) for a magnetic levitation system (MLS) based on the linear feedforward control method combined with FLC. MLS has many applications in industry, transportation, but the system is strongly nonlinear and unstable at equilibrium. The fast response linear control law ensures that the ball is kept at the desired point, but does not remain stable at that point in the presence of noise or deviation from the desired position. The controller that combines linear feedforward control and FLC is designed to ensure ball stability and increase the system's fast-response when deviating from equilibrium and improve control quality. Simulation results in the presence of noise show that the proposed control law has a fast and stable effect on external noise. The advantages of the proposed controller are shown through the comparison results with conventional PID and FLC control laws

IMPLEMENTATION OF CONTROL ALGORITHMS IN BALL MAGNETIC LEVITATION SYSTEM TO IMPROVE SYSTEM PARAMETERS

Magnetic Levitation System (Maglev) is an approach which is currently widely applied in different areas like semiconductor, transportation, power generation, household appliances and etc. Since Magnetic Levitation System is a highly non-linear system, constructing a successful controller which has robust performance becomes a big challenge. The most conventional method of building Maglev is PID controller. However findings of controller’s parameters which ar

Two-Dimensional Fuzzy Sliding Mode Control of a Field-Sensed Magnetic Suspension System

This paper presents the two-dimensional fuzzy sliding mode control of a field-sensed magnetic suspension system. The fuzzy rules include both the sliding manifold and its derivative. The fuzzy sliding mode control has advantages of the sliding mode control and the fuzzy control rules are minimized. Magnetic suspension systems are nonlinear and inherently unstable systems. The two-dimensional fuzzy sliding mode control can stabilize the nonlinear systems globally and attenuate chatter effectively. It is adequate to be applied to magnetic suspension systems. New design circuits of magnetic suspension systems are proposed in this paper. ARM Cortex-M3 microcontroller is utilized as a digital controller. The implemented driver, sensor, and control circuits are simpler, more inexpensive, and effective. This apparatus is satisfactory for engineering education. In the hands-on experiments, the proposed control scheme markedly improves performances of the field-sensed magnetic suspension system

Fuzzy sliding control with non-linear observer for magnetic levitation systems

© 2016 IEEE. Magnetic levitation (Maglev) systems make significant contribution to industrial applications due their reduced power consumption, increased power efficiency and reduced cost of maintenance. Common applications include Maglev power generation (e.g. wind turbine), Maglev trains and medical devices (e.g. magnetically suspended artificial heart pump). This paper proposes fuzzy sliding-mode controller 'FSMC' with a nonlinear observer been used to estimate the unmeasured states. Simulations are performed with nonlinear mathematical model of the Maglev system, and the results show that the proposed observer and control strategy perform well

A Novel Fuzzy Logic Based Adaptive Supertwisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness of the proposed controller over the first order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on a DC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desired transient response without causing chattering and error under steady-state conditions. The proposed controller is able to give robust performance in terms of rejection to input voltage variations and load variations.Comment: 14 page

Rotors on Active Magnetic Bearings: Modeling and Control Techniques

In the last decades the deeper and more detailed understanding of rotating machinery dynamic behavior facilitated the study and the design of several devices aiming at friction reduction, vibration damping and control, rotational speed increase and mechanical design optimization. Among these devices a promising technology is represented by active magnetic actuators which found a great spread in rotordynamics and in high precision applications due to (a) the absence of all fatigue and tribology issues motivated by the absence of contact, (b) the small sensitivity to the operating conditions, (c) the wide possibility of tuning even during operation, (d) the predictability of the behavior. This technology can be classified as a typical mechatronic product due to its nature which involves mechanical, electrical and control aspects, merging them in a single system. The attractive potential of active magnetic suspensions motivated a considerable research effort for the past decade focused mostly on electrical actuation subsystem and control strategies. Examples of application areas are: (a) Turbomachinery, (b) Vibration isolation, (c) Machine tools and electric drives, (d) Energy storing flywheels, (e) Instruments in space and physics, (f) Non-contacting suspensions for micro-techniques, (g) Identification and test equipment in rotordynamics. This chapter illustrates the design, the modeling, the experimental tests and validation of all the subsystems of a rotors on a five-axes active magnetic suspension. The mechanical, electrical, electronic and control strategies aspects are explained with a mechatronic approach evaluating all the interactions between them. The main goals of the manuscript are: • Illustrate the design and the modeling phases of a five-axes active magnetic suspension; • Discuss the design steps and the practical implementation of a standard suspension control strategy; • Introduce an off-line technique of electrical centering of the actuators; • Illustrate the design steps and the practical implementation of an online rotor selfcentering control technique. The experimental test rig is a shaft (Weight: 5.3 kg. Length: 0.5 m) supported by two radial and one axial cylindrical active magnetic bearings and powered by an asynchronous high frequency electric motor. The chapter starts on an overview of the most common technologies used to support rotors with a deep analysis of their advantages and drawbacks with respect to active magnetic bearings. Furthermore a discussion on magnetic suspensions state of the art is carried out highlighting the research efforts directions and the goals reached in the last years. In the central sections, a detailed description of each subsystem is performed along with the modeling steps. In particular the rotor is modeled with a FE code while the actuators are considered in a linearized model. The last sections of the chapter are focused on the control strategies design and the experimental tests. An off-line technique of actuators electrical centering is explained and its advantages are described in the control design context. This strategy can be summarized as follows. Knowing that: a) each actuation axis is composed by two electromagnets; b) each electromagnet needs a current closed-loop control; c) the bandwidth of this control is depending on the mechanical airgap, then the technique allows to obtain the same value of the closed-loop bandwidth of the current control of both the electromagnets of the same actuation axis. This approach improves performance and gives more steadiness to the control behavior. The decentralized approach of the control strategy allowing the full suspensions on five axes is illustrated from the design steps to the practical implementation on the control unit. Furthermore a selfcentering technique is described and implemented on the experimental test rig: this technique uses a mobile notch filter synchronous with the rotational speed and allows the rotor to spin around its mass center. The actuators are not forced to counteract the unbalance excitation avoiding saturations. Finally, the experimental tests are carried out on the rotor to validate the suspension control, the off-line electrical centering and the selfcentering technique. The numerical and experimental results are superimposed and compared to prove the effectiveness of the modeling approach

Design, Optimization, and Experimental Characterization of a Novel Magnetically Actuated Finger Micromanipulator

The ability of external magnetic fields to precisely control micromanipulator systems has received a great deal of attention from researchers in recent years due to its off-board power source. As these micromanipulators provide frictionless motion, and precise motion control, they have promising potential applications in many fields. Conversely, major drawbacks of electromagnetic micromanipulators, include a limited motion range compared to the micromanipulator volume, the inability to handle heavy payloads, and the need for a large drive unit compared to the size of the levitated object, and finally, a low ratio of the generated magnetic force to the micromanipulator weight. To overcome these limitations, we designed a novel electromagnetic finger micromanipulator that was adapted from the well-known spherical robot. The design and optimization procedures for building a three Degree of Freedoms (DOF) electromagnetic finger micromanipulator are firstly introduced. This finger micromanipulator has many potential applications, such as cell manipulation, and pick and place operations. The system consists of two main subsystems: a magnetic actuator, and an electromagnetic end-effector that is connected to the magnetic actuator by a needle. The magnetic actuator consists of four permanent magnets and four electromagnetic coils that work together to guide the micromanipulator finger in the xz plane. The electromagnetic end-effector consists of a rod shape permanent magnet that is aligned along the y axis and surrounded by an electromagnetic coil. The optimal configuration that maximizes the micromanipulator actuation force, and a closed form solution for micromanipulator magnetic actuation force are presented. The model is verified by measuring the interaction force between an electromagnet and a permanent magnet experimentally, and using Finite Element Methods (FEM) analysis. The results show an agreement between the model, the experiment, and the FEM results. The error difference between the FEM, experimental, and model data was 0.05 N. The micromanipulator can be remotely operated by transferring magnetic energy from outside, which means there is no mechanical contact between the actuator and the micromanipulator. Moreover, three control algorithms are designed in order to compute control input currents that are able to control the position of the end-effector in the x, y, and z axes. The proposed controllers are: PID controller, state-feedback controller, and adaptive controller. The experimental results show that the micromanipulator is able to track the desired trajectory with a steady-state error less than 10 µm for a payload free condition. Finally, the ability of the micromanipulator to pick-and-place unknown payloads is demonstrated. To achieve this objective, a robust model reference adaptive controller (MRAC) using the MIT rule for an adaptive mechanism to guide the micromanipulator in the workspace is implemented. The performance of the MRAC is compared with a standard PID controller and state-feedback controller. For the payload free condition, the experimental results show the ability of the micromanipulator to follow a desired motion trajectory in all control strategies with a root mean square error less than 0.2 mm. However, while there is payload variation, the PID controller response yields a non smooth motion with a large overshoot and undershoot. Similarly, the state-feedback controller suffers from variability of dynamics and disturbances due to the payload variation, which yields to non-smooth motion and large overshoot. The micromanipulator motion under the MRAC control scheme conversely follows the desired motion trajectory with the same accuracy. It is found that the micromanipulator can handle payloads up to 75 grams and it has a motion range of ∓ 15 mm in all axes