Optimised configuration of sensors for fault tolerant control of an electro-magnetic suspension system

For any given system the number and location of sensors can affect the closed-loop performance as well as the reliability of the system. Hence, one problem in control system design is the selection of the sensors in some optimum sense that considers both the system performance and reliability. Although some methods have been proposed that deal with some of the aforementioned aspects, in this work, a design framework dealing with both control and reliability aspects is presented. The proposed framework is able to identify the best sensor set for which optimum performance is achieved even under single or multiple sensor failures with minimum sensor redundancy. The proposed systematic framework combines linear quadratic Gaussian control, fault tolerant control and multiobjective optimisation. The efficacy of the proposed framework is shown via appropriate simulations on an electro-magnetic suspension system

Optimised configuration of sensing elements for control and fault tolerance applied to an electro-magnetic suspension system

New technological advances and the requirements to increasingly abide by new safety laws in engineering design projects highly affects industrial products in areas such as automotive, aerospace and railway industries. The necessity arises to design reduced-cost hi-tech products with minimal complexity, optimal performance, effective parameter robustness properties, and high reliability with fault tolerance. In this context the control system design plays an important role and the impact is crucial relative to the level of cost efficiency of a product. Measurement of required information for the operation of the design control system in any product is a vital issue, and in such cases a number of sensors can be available to select from in order to achieve the desired system properties. However, for a complex engineering system a manual procedure to select the best sensor set subject to the desired system properties can be very complicated, time consuming or even impossible to achieve. This is more evident in the case of large number of sensors and the requirement to comply with optimum performance. The thesis describes a comprehensive study of sensor selection for control and fault tolerance with the particular application of an ElectroMagnetic Levitation system (being an unstable, nonlinear, safety-critical system with non-trivial control performance requirements). The particular aim of the presented work is to identify effective sensor selection frameworks subject to given system properties for controlling (with a level of fault tolerance) the MagLev suspension system. A particular objective of the work is to identify the minimum possible sensors that can be used to cover multiple sensor faults, while maintaining optimum performance with the remaining sensors. The tools employed combine modern control strategies and multiobjective constraint optimisation (for tuning purposes) methods. An important part of the work is the design and construction of a 25kg MagLev suspension to be used for experimental verification of the proposed sensor selection frameworks

A prototype of an energy-efficient MAGLEV train : a step towards cleaner train transport

The magnetic levitation (MAGLEV) train uses magnetic field to suspend, guide, and propel vehicle onto the track. The MAGLEV train provides a sustainable and cleaner solution for train transportation by significantly reducing the energy usage and greenhouse gas emissions as compared to traditional train transportation systems. In this paper, we propose an advanced control mechanism using an Arduino microcontroller that selectively energizes the electromagnets in a MAGLEV train system to provide dynamic stability and energy efficiency. We also design the prototype of an energy-efficient MAGLEV train that leverages our proposed control mechanism. In our MAGLEV train prototype, the levitation is achieved by creating a repulsive magnetic field between the train and the track using magnets mounted on the top-side of the track and bottom-side of the vehicle. The propulsion is performed by creating a repulsive magnetic field between the permanent magnets attached on the sides of the vehicle and electromagnets mounted at the center of the track using electrodynamic suspension (EDS). The electromagnets are energized via a control mechanism that is applied through an Arduino microcontroller. The Arduino microcontroller is programmed in such a way to propel and guide the vehicle onto the track by appropriate switching of the electromagnets. We use an infrared-based remote-control device for controlling the power, speed, and direction of the vehicle in both the forward and the backward direction. The proposed MAGLEV train control mechanism is novel, and according to the best of our knowledge is the first study of its kind that uses an Arduino-based microcontroller system for control mechanism. Experimental results illustrate that the designed prototype consumes only 144 W-hour (Wh) of energy as compared to a conventionally designed MAGLEV train prototype that consumes 1200 Wh. Results reveal that our proposed control mechanism and prototype model can reduce the total power consumption by 8.3 x as compared to the traditional MAGLEV train prototype, and can be applied to practical MAGLEV trains with necessary modifications. Thus, our proposed prototype and control mechanism serves as a first step towards cleaner engineering of train transportation systems

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

Multilevel Converters: An Enabling Technology for High-Power Applications

| Multilevel converters are considered today as the state-of-the-art power-conversion systems for high-power and power-quality demanding applications. This paper presents a tutorial on this technology, covering the operating principle and the different power circuit topologies, modulation methods, technical issues and industry applications. Special attention is given to established technology already found in industry with more in-depth and self-contained information, while recent advances and state-of-the-art contributions are addressed with useful references. This paper serves as an introduction to the subject for the not-familiarized reader, as well as an update or reference for academics and practicing engineers working in the field of industrial and power electronics.Ministerio de Ciencia y Tecnología DPI2001-3089Ministerio de Eduación y Ciencia d TEC2006-0386

Superconductivity and their applications

Trabalho apresentado em International Conference on Renewable Energies and Power Quality (ICREPQ’17), 4 a 6 de Abril de 2017, Málaga, EspanhaThe research in the field of superconductivity has led to the synthesis of superconducting materials with features that allow you to expand the applicability of this kind of materials. Among the superconducting materials characteristics, the critical temperature of the superconductor is framing the range and type of industrial applications that can benefit from them. Some examples of industrial applications incorporating superconducting materials stand out in this paper. Among other possibilities, the nuclear magnetic resonance, the magnetic levitation train, the transport processing of electrical energy (motors, generators, transformers and power lines) and superconducting magnetic energy storage (SMES) systems are already solutions contributing to the nowadays daily life, but more than that, are solutions that will contribute to improve the quality of life of many human beings in the near future. In addition to these solutions, in this paper are presented and discussed the pros and cons of a solution designed for the fast field cycling nuclear magnetic resonance technique that benefits of the usage of superconducting blocks.N/

Robustness and Control of a Magnetically Levitated Transportation System

Electromagnetic suspension of Magnetic Levitation Vehicles (Maglev) has been studied for many years as an alternative to wheel-on rail transportation systems. In this work, design and implementation of control systems for a Maglev laboratory experiment and a Maglev vehicle under development at Old Dominion University are described. Both plants are modeled and simulated with consideration of issues associated with system non-linearity, structural flexibility and electromagnetic force modeling. Discussion concerning different control strategies, namely centralized and decentralized approaches are compared and contrasted in this work. Different types of electromagnetic non-linearities are considered and described to establish a convenient method for modeling such a system. It is shown how a Finite Element structural model can be incorporated into the system to obtain transfer function notation. Influence of the dynamic interaction between the Maglev track and the Maglev vehicle is discussed and supported by both analytical results and theoretical examples. Finally, several control laws designed to obtain stable and robust levitation are explored in detail

Fault tolerant computer control for a Maglev transportation system

Magnetically levitated (Maglev) vehicles operating on dedicated guideways at speeds of 500 km/hr are an emerging transportation alternative to short-haul air and high-speed rail. They have the potential to offer a service significantly more dependable than air and with less operating cost than both air and high-speed rail. Maglev transportation derives these benefits by using magnetic forces to suspend a vehicle 8 to 200 mm above the guideway. Magnetic forces are also used for propulsion and guidance. The combination of high speed, short headways, stringent ride quality requirements, and a distributed offboard propulsion system necessitates high levels of automation for the Maglev control and operation. Very high levels of safety and availability will be required for the Maglev control system. This paper describes the mission scenario, functional requirements, and dependability and performance requirements of the Maglev command, control, and communications system. A distributed hierarchical architecture consisting of vehicle on-board computers, wayside zone computers, a central computer facility, and communication links between these entities was synthesized to meet the functional and dependability requirements on the maglev. Two variations of the basic architecture are described: the Smart Vehicle Architecture (SVA) and the Zone Control Architecture (ZCA). Preliminary dependability modeling results are also presented

Optimised configuration of sensors for fault tolerant control of an electro-magnetic suspension system

For any given system the number and location of sensors can affect the closed-loop performance as well as the reliability of the system. Hence, one problem in control system design is the selection of the sensors in some optimum sense that considers both the system performance and reliability. Although some methods have been proposed that deal with some of the aforementioned aspects, in this work, a design framework dealing with both control and reliability aspects is presented. The proposed framework is able to identify the best sensor set for which optimum performance is achieved even under single or multiple sensor failures with minimum sensor redundancy. The proposed systematic framework combines linear quadratic Gaussian control, fault tolerant control and multiobjective optimisation. The efficacy of the proposed framework is shown via appropriate simulations on an electro-magnetic suspension system