Fault Detection Based on Tracking Differentiator Applied on the Suspension System of Maglev Train

A fault detection method based on the optimized tracking differentiator is introduced. It is applied on the acceleration sensor of the suspension system of maglev train. It detects the fault of the acceleration sensor by comparing the acceleration integral signal with the speed signal obtained by the optimized tracking differentiator. This paper optimizes the control variable when the states locate within or beyond the two-step reachable region to improve the performance of the approximate linear discrete tracking differentiator. Fault-tolerant control has been conducted by feedback based on the speed signal acquired from the optimized tracking differentiator when the acceleration sensor fails. The simulation and experiment results show the practical usefulness of the presented method

Time Delay Compensation for Tracking Differentiator and Its Application on Phase Sensor

Abstract: This study shows the time delay compensation for tracking differentiator and its application on phase sensor. Filtering time delay compensation algorithm for phase sensor of high speed maglev train with Electromagnetic Suspension (EMS) system is studied. Firstly, the structure and functions of the sensor are introduced. Secondly, the reasons for the phase signal distortion are analyzed. Then, a kind of nonlinear Tracking Differentiator (TD) is introduced. The time delay characteristics of the nonlinear TD are studied and the time delay constant is figured out approximately. Then, a compensation algorithm is proposed based on phase forecasting. At last the TD and its compensation algorithms are applied to the phase signal to improve the waveform. The experimental results show that the designed algorithm is effective

Improved active disturbance rejection controller for rotor system of magnetic levitation turbomachinery

The rotor of the magnetic suspension turbomachinery is supported by the magnetic suspension bearing without contact and mechanical friction, which directly drives the high-efficiency fluid impeller. It has the advantages of high efficiency, low noise, less fault and no lubrication. However, the system often has some unknown mutation, time variation, load perturbation and other un-certainties when working, and the traditional Proportion Integration Differentiation (PID) control strategy has great limitations to overcome the above disturbances. Therefore, this paper firstly establishes a mathematical model of the rotor of magnetic levitation turbomachinery. Then, a linear active disturbance rejection controller (LADRC) is presented, which can not only improve the above problems of PID control, but also avoid the complex parameter tuning process of traditional nonlinear active disturbance rejection control (ADRC). However, LADRC is easy to induce the overshoot of the system and cannot filter the given signal. On this basis, an improved LADRC with a fast-tracking differentiator (FTD) is proposed to arrange the transition process of input signals. The simulation results show that compared with the traditional PID controller and single LADRC, the improved linear active disturbance rejection control method with fast tracking differentiator (FTD-LADRC) can better suppress some unknown abrupt changes, time variation and other uncertainties of the electromagnetic bearing-rotor system. At the same time, the overshoot of the system is smaller, and the parameters are easy to be set, which is convenient for engineering application

Sliding mode differentiator via improved adaptive notch filter

summary:To tackle the difficulty in tuning the parameters of sliding mode differentiator (SMD), an improved adaptive notch filter based real-time parameter tuning scheme (denoted as ANF-SMD) is presented. Specifically, the integral feedback of the system output errors is introduced in constructing the cost function for the adaptive notch filter so as to estimate the real-time amplitude and frequency of given inputs. Then, upon the deterministic formula between the parameters of the SMD and the input signals, the parameters of the SMD can be adjusted adaptively as inputs vary. Simulation results show that the proposed ANF-SMD scheme performs well in signal filtering and differentiation estimation. The effectiveness of the proposed ANF-SMD is further experimentally verified on the pressure signal processing for the altitude ground test facility

Third International Symposium on Magnetic Suspension Technology

In order to examine the state of technology of all areas of magnetic suspension and to review recent developments in sensors, controls, superconducting magnet technology, and design/implementation practices, the Third International Symposium on Magnetic Suspension Technology was held at the Holiday Inn Capital Plaza in Tallahassee, Florida on 13-15 Dec. 1995. The symposium included 19 sessions in which a total of 55 papers were presented. The technical sessions covered the areas of bearings, superconductivity, vibration isolation, maglev, controls, space applications, general applications, bearing/actuator design, modeling, precision applications, electromagnetic launch and hypersonic maglev, applications of superconductivity, and sensors

Magnetic suspension techniques for precision motion control

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1990.Includes bibliographical references (leaves 256-263).by David Lippincott Trumper.Ph.D

A simple discrete-time tracking differentiator and its application to speed and position detection system for a maglev train

In this brief, a novel tracking differentiator (TD) based on discrete time optimal control (DTOC) is presented. In particular, using the state back-stepping method, a DTOC law for a discrete-time, double-integral system is determined by linearized criterion, which equips the TD with a simple structure. The analysis of the proposed TD reveals its filtering mechanism. Simulation results show that it performs well in signal tracking and differentiation acquisition, and reduces the computational resources needed. Experiments conducted on the speed and position detection system for a maglev train demonstrate that the proposed TD group, with moving average algorithm, can filter noises, amend distortion signals effectively, and compensate for phase delays when the train is passing over track joints.NRF (Natl Research Foundation, S’pore)MOE (Min. of Education, S’pore)Accepted versio