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Öğe Electric fault diagnosis and detection in an induction machine using RMS based method(Institute of Electrical and Electronics Engineers Inc., 2022) Akrad, Ahmad; Sehab, Rabia; Alyoussef, FadiNowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a new method is developed for fault detection using residual errors generated by the root mean square (RMS) of phase currents. This approach is based on an asymmetric nonlinear model of Induction Machine where the winding fault of the three axes frame state space is taken into account. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults. © 2022 IEEE.Öğe Robust PI-PD controller design: Industrial simulation case studies and a real-time application(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Alyoussef, Fadi; Kaya, İbrahim; Akrad, AhmadPI-PD controllers have superior performance compared to traditional PID controllers, especially for controlling unstable and integrating industrial processes with time delays. However, computing the four tuning parameters of this type of controller is not an easy task. Recently, there has been significant interest in determining the tuning rules for PI-PD controllers that utilize the stability region. Currently, most tuning rules for the PI-PD controller are presented graphically, which can be time-consuming and act as a barrier to their industrial application. There is a lack of analytical tuning guidelines in the literature to address this shortfall. However, the existing analytical tuning guidelines do not consider a rigorous design approach. This work proposes new robust analytical tuning criteria based on predefined gain and phase margin bounds, as well as the centroid of the stability region. The proposed method has been tested using various simulation studies related to a DC–DC buck converter, a DC motor, and a heat exchanger. The results indicate that the proposed tuning rules exhibit strong performance against parameter uncertainty with minimal overshoots. Furthermore, the suggested technique for simultaneous control of yaw and pitch angles has been tested in a real-time application using the twin rotor multi-input multi-output system (TRMS). Real-time results indicate that, compared to other methods under investigation, the suggested approach provides nearly minimal overshoots.Öğe Speed Sensor Fault-Tolerant Controller for Induction Motor Using New Minimum Probability Voter Based on Signal Strength(Ieee, 2019) Alyoussef, Fadi; Akrad, AhmadA speed sensor fault-tolerant back-stepping controller with a new minimum probability voter based on signal strength (MPVSS) has been introduced in this paper. The major goal of MPVSS is to detect and to reconfigure the induction motor control in case of speed sensor failure (intermittent disconnection of an incremental encoder) using sliding mode observer for low speed estimation and extended Kalman filter for medium and high speed estimation. Here, the proposed MPVSS enjoys the feature of insensitivity to rotor resistance variations and easiness to set its threshold. In fact, signal strength plays an essential role in releasing the designer from severe constraints imposed by selecting a correct voter threshold. Simulation results show the efficiency of the suggested method. Besides, the superiority of the presented approach has been confirmed by comparing its performance with a maximum-likelihood voting algorithm.Öğe Velocity sensor fault-tolerant controller for induction machine using intelligent voting algorithm(MDPI, 2022) Alyoussef, Fadi; Akrad, Ahmad; Sehab, Rabia; Morel, Cristina; Kaya, İbrahimNowadays, induction machines (IMs) are widely used in industrial and transportation applications (electric or hybrid ground vehicle or aerospace actuators) thanks to their significant advantages in comparison to other technologies. Indeed, there is a large demand for IMs because of their reliability, robustness, and cost-effectiveness. The objective of this paper is to improve the reliability and performance of the three-phase induction machine in case of mechanical sensor failure. Moreover, this paper will discuss the development and proposal of a fault-tolerant controller (FTC), based on the combination of a vector controller, two virtual sensors (an extended Kalman filter, or EKF, and a sliding mode observer, or SMO) and a neural voting algorithm. In this approach, the vector controller is based on a new structure of a back-stepping sliding mode controller, which incorporates a double integral sliding surface to improve the performance of the induction machine in faulty operation mode. More specifically, this controller improves the machine performance in terms of having a fast response, fewer steady-state errors, and a robust performance in the existence of uncertainty. In addition, two voting algorithms are suggested in this approach. The first is based on neural networks, which are insensitive to parameter variations and do not need to set a threshold. The second one is based on fuzzy logic. Finally, validation is carried out by simulations in healthy and faulty operation modes to prove the feasibility of the proposed FTC.
