Interval Observer and Unknown Input Observer-based Sensor Fault Estimation for High-speed Railway Traction Motor

In this paper, fault estimation for high-speed railway traction motor with sensor fault and disturbances is investigated based on the interval observer and unknown input observer (IO-UIO). First, the proposed method, which can completely eliminate the external disturbance, is studied based on the disturbance isolation characteristic of the unknown input observer. Then, an interval observer is constructed to deal with the nonlinear part, which sandwiched the actual system between the upper and lower bounds. Moreover, the Metzler matrix is constructed using an equivalent transformation and through the unified design based on the concept of the augmented state to form a global fault augmented model. Finally, simulation results are presented to illustrate the effectiveness and advantages of the proposed IO-UIO

A Hybrid Sensor Fault Diagnosis for Maintenance in Railway Traction Drives

Due to the importance of sensors in railway traction drives availability, sensor fault diagnosis has become a key point in order tomove frompreventivemaintenance to condition-basedmaintenance. Most research works are limited to sensor fault detection and isolation, but only a few of them analyze the types of sensor faults, such as offset or gain, with the aim of reconfiguring the sensor in order to implement a fault tolerant system. This article is based on a fusion of model-based and data-driven techniques. First, an observer-based approach, using a Sliding Mode observer, is utilized for sensor fault reconstruction in real time. Then, once the fault is detected, a timewindowof sensormeasurements and sensor fault reconstruction is sent to the remotemaintenance center for fault evaluation. Finally, an offline processing is carried out to discriminate between gain and offset sensor faults, in order to get a maintenance decision-making to reconfigure the sensor during the next train stop. Fault classification is done by means of histograms and statistics. The technique here proposed is applied to the DC-link voltage sensor in a railway traction drive and is validated in a hardware-in-the-loop platform

A Review in Fault Diagnosis and Health Assessment for Railway Traction Drives

During the last decade, due to the increasing importance of reliability and availability, railway industry is making greater use of fault diagnosis approaches for early fault detection, as well as Condition-based maintenance frameworks. Due to the influence of traction drive in the railway system availability, several research works have been focused on Fault Diagnosis for Railway traction drives. Fault diagnosis approaches have been applied to electric machines, sensors and power electronics. Furthermore, Condition-based maintenance framework seems to reduce corrective and Time-based maintenance works in Railway Systems. However, there is not any publication that summarizes all the research works carried out in Fault diagnosis and Condition-based Maintenance frameworks for Railway Traction Drives. Thus, this review presents the development of Health Assessment and Fault Diagnosis in Railway Traction Drives during the last decade

Interval Sliding Mode Observer based Fault Accommodation for Non-minimum Phase LPV Systems with Online Control Allocation

This paper proposes an interval sliding mode observer (ISMO) based sliding mode actuator fault accommodation (FA) framework for non-minimum phase linear-parameter-varying (LPV) systems involving online control allocation (CA) problem. Firstly, a specifically designed coordinate transformation is introduced to deal with the non-minimum phase issue. Then, for the transformed system, an ISMO is proposed to estimate the set of admissible values for the states of the faulty LPV systems. It is constructed based on the designed interval bounds for the scheduling-parameter-related uncertainties and fault-related items. The observer is designed by combining the interval observer and the sliding mode observer techniques. A fault-tolerant control (FTC) law with an online CA scheme is subsequently designed by stabilizing the proposed ISMO instead of the original faulty LPV system, which guarantees that the unmeasurable states of the original LPV system converge to zero asymptotically, the measurable outputs converge to zero in finite time, and further, the actual control efforts are allocated to all actuators optimally and satisfy prescribed performance. Finally, a simulation based on the inverter used in China Railway High-speed (CRH) is presented to illustrate the effectiveness of the proposed framework

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines

No-Tension Sensor Closed-Loop Control Method with Adaptive PI Parameters for Two-Motor Winding System

In a winding system, it is very important to control the tension precisely. Based on the process of rewinding and unwinding, a sensorless tension control method with PI parameters of adaptive speed controllers is proposed in this paper. According to the principle of torque balance, a tension observer is designed to replace the tension sensor, and the observed value instead of the measured value of tension is used as feedback. Then the measurement delay caused by tension sensor is reduced. For the time-variable inertia, Landau discrete-time recursive algorithm is used to estimate the inertias of the rewind and unwind motors. Moreover, the estimated inertias are used to adjust the PI parameters of the speed controllers. As the tension control system has the ability to adapt to the change of inertia, its dynamic performance is improved to some extent. In addition, the proposed sensorless tension control method is simple and easy to implement, which only uses the current and speed signals of the motors without any additional hardware needed. At last, the feasibility and effectiveness of the proposed method are verified by the experimental results

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering

Industrial and Technological Applications of Power Electronics Systems

The Special Issue "Industrial and Technological Applications of Power Electronics Systems" focuses on: - new strategies of control for electric machines, including sensorless control and fault diagnosis; - existing and emerging industrial applications of GaN and SiC-based converters; - modern methods for electromagnetic compatibility. The book covers topics such as control systems, fault diagnosis, converters, inverters, and electromagnetic interference in power electronics systems. The Special Issue includes 19 scientific papers by industry experts and worldwide professors in the area of electrical engineering

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance