Control approaches for magnetic levitation systems and recent works on its controllers’ optimization: a review

Magnetic levitation (Maglev) system is a stimulating nonlinear mechatronic system in which an electromagnetic force is required to suspend an object (metal sphere) in the air. The electromagnetic force is very sensitive to the noise, which can create acceleration forces on the metal sphere, causing the sphere to move into the unbalanced region. Maglev benefits the industry since 1842, in which the maglev system has reduced power consumption, increased power efficiency, and reduced maintenance cost. The typical applications of Maglev system are in wind turbine for power generation, Maglev trains and medical tools. This paper presents a comparative assessment of controllers for the maglev system and ways for optimally tuning the controllers’ parameters. Several types of controllers for maglev system are also reviewed throughout this paper

Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model\u27s parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov\u27s stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously

A Hybrid Controller for Stability Robustness, Performance Robustness, and Disturbance Attenuation of a Maglev System

Devices using magnetic levitation (maglev) offer the potential for friction-free, high-speed, and high-precision operation. Applications include frictionless bearings, high-speed ground transportation systems, wafer distribution systems, high-precision positioning stages, and vibration isolation tables. Maglev systems rely on feedback controllers to maintain stable levitation. Designing such feedback controllers is challenging since mathematically the electromagnetic force is nonlinear and there is no local minimum point on the levitating force function. As a result, maglev systems are open-loop unstable. Additionally, maglev systems experience disturbances and system parameter variations (uncertainties) during operation. A successful controller design for maglev system guarantees stability during levitating despite system nonlinearity, and desirable system performance despite disturbances and system uncertainties. This research investigates five controllers that can achieve stable levitation: PD, PID, lead, model reference control, and LQR/LQG. It proposes an acceleration feedback controller (AFC) design that attenuates disturbance on a maglev system with a PD controller. This research proposes three robust controllers, QFT, Hinf , and QFT/Hinf , followed by a novel AFC-enhanced QFT/Hinf (AQH) controller. The AQH controller allows system robustness and disturbance attenuation to be achieved in one controller design. The controller designs are validated through simulations and experiments. In this research, the disturbances are represented by force disturbances on the levitated object, and the system uncertainties are represented by parameter variations. The experiments are conducted on a 1 DOF maglev testbed, with system performance including stability, disturbance rejection, and robustness being evaluated. Experiments show that the tested controllers can maintain stable levitation. Disturbance attenuation is achieved with the AFC. The robust controllers, QFT, Hinf , QFT/ Hinf, and AQH successfully guarantee system robustness. In addition, AQH controller provides the maglev system with a disturbance attenuation feature. The contributions of this research are the design and implementation of the acceleration feedback controller, the QFT/ Hinf , and the AQH controller. Disturbance attenuation and system robustness are achieved with these controllers. The controllers developed in this research are applicable to similar maglev systems

Application of local approximators for control of real mechatronic system

Cieľom práce je aplikácia lokálnych aproximátorov pre riadenie reálnych mechatronických sústav pomocou metódy dopredného riadenia predstavujúcej zaujímavú alternatívu k metódam využívajúcim globálne aproximátory. Po ukážkových príkladoch funkcie lokálnych aproximátorov bol navrhnutý algoritmus implementovaný pre riadenie dvoch sústav, elektronickej škrtiacej klapky a výukového modelu magnetickej levitácie, predstavujúcich vysoko nelineárne a nestabilné sústavy. Skúmali sme, či riadiaci algoritmus bude mať pozitívny vplyv na presnosť regulácie, ďalej bola skúmaná jeho schopnosť prispôsobiť sa zmene parametrov sústavy a tiež prípadná možnosť jeho implementácie pre mikrokontrolér znížením vzorkovacej frekvencie. Výsledky ukázali, že riadenie založené na lokálnych modeloch zlepšilo riadenie v porovnaní s jednoduchým PID regulátorom a že má schopnosť adaptability. Veľmi výhodné sa zdá byť jeho použitie pre zariadenia umožnujúce vzorkovaciu frekvenciu do 1 kHz.The main aim of this thesis is application of local approximators for control of real mechatronic systems by means of feed-forward control which represents a promising alternative to methods utilizing global approximators. After instances of how local approximators work they were implemented for control of two plants: electronic throttle and educational model of magnetic levitation, which both represent highly non-linear and unstable systems. It was observed whether the designed algorithm would improve the regulation accuracy, further its adaptability to to the plant's parameter change was tested and nally the convenience of its implementation for MCU was observed by lowering sample frequency. The results shows that local-models based control have improved regulation in comparison with PID used alone and that it is adaptable. Moreover, its utilization by MCUs providing sample frequency up to 1 kHz seems to be very advantageous.

Sliding Mode Control for Bearingless Induction Motor Based on a Novel Load Torque Observer

For the problem of low control performance of Bearingless Induction Motor (BIM) control system in the presence of large load disturbance, a novel load torque sliding mode observer is proposed on the basis of establishing sliding mode speed control system. The load observer chooses the speed and load torque of the BIM control system as the observed objects, uses the speed error to design the integral sliding mode surface, and adds the low-pass filter to reduce the torque observation error. Meanwhile, the output of the load torque is used as the feedforward compensation for the control system, which can provide the required current for load changes and reduce the adverse influence of disturbance on system performance. Besides, considering that the load changes lead to the varying rotational inertia, the integral identification method is adopted to identify the rotational inertia of BIM, and the rotational inertia can be updated to the load observer in real time. The simulation and experiment results all show that the proposed method can track load torque accurately, improve the ability to resist disturbances, and ameliorate the operation quality of BIM control system. The chattering of sliding mode also is suppressed effectively

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

Feasibility assessment of a Kalman filter approach to fault detection and fault-tolerance in a highly unstable system: The RIT heart pump

The purpose of this project is to assess the feasibility of a Kalman Filter approach for fault detection in a highly unstable system, specifically the heart pump currently under development at RIT. Simulations and experimental work were completed to determine the effects of possible position sensor fault conditions on the system; that information was then used in conjunction with a pair of Kalman filters to create a method of detecting faults and providing fault-tolerant operation. The heart pump system was modeled using Simulink and then the fault diagnosis and tolerance system was added to the model and tested via simulation in SIMULINK TM. The simulations showed the filters were able to calculate and remove bias caused by any type of position sensor error, provided the estimated plant model is nearly identical to the actual plant model. Sensitivity analysis showed that the fault detection/fault-tolerance method is extremely sensitive to discrepancies between the estimated plant model and actual pump behavior. Because of this, it is considered unfeasible for implementation on a real system. Experimental results confirmed these findings, demonstrating the drawbacks of model-based fault detection and tolerance methods