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Persistent anomalies in modern photovoltaic (PV) systems present a formidable challenge, impeding optimal power output and system resilience. Artificial Intelligence (AI) has surfaced as a game-changing solution, yet existing research has merely scratched the surface of solar panel prognosis, leaving a critical void in leveraging AI’s explainable nature and active learning capabilities. This pioneering study…

This paper presents a new observer-based method which deals with the extraction of amplitude of characteristic frequencies for the fault diagnosis in permanent magnet synchronous motors (PMSM). First, a pilot survey is made to investigate the typical harmonics in the line currents of PMSM. Second, an appropriate structure of observer is formulated with the input…

The integration of renewable energy distributed generation (REDG) into the energized distribution power grid has become more popular in recent years. This has been escalated by the general global energy shortages. The REDG has proven to be effective for energy sustainability and reliability. However, there are technical challenges which arise from integrating REDG into the…

Recently, the number of industrial accidents of chemical plants has been increasing in Japan. The fault detection system is required to keep chemical plant safely. In this study, a fault detection system for a chemical plant using agent framework and negative selection algorithm was proposed. The negative selection algorithm is one of artificial immune systems.…

The transmission network has been considered among the globe’s prevalent complex systems, comprised of hundreds of electrical transmission lines and other equipment used to transmit electrical energy from one location to another. Over a decade, power engineers have worked tirelessly to ensure that the transmission network operates reliably, transmitting electrical energy from the power station…

This paper presents an integrated solution for a fault-tolerant three-phase permanent magnet synchronous motor (PMSM) field-oriented control drive subjected to an open-phase fault (OPF) integrated with effective fault-tolerant detection methodology. The fault detection methodology is based on model predictive current control (MPCC), which is easy to apply, detect OPF in a range of microseconds, and…

Bearings are the key components of many rotating machines, in which serious failure or even major breakdown may occur due to their abnormal operation and defects. Thus, accurate fault diagnoses of bearing elements are essential for proactive predictive maintenance. However, the using of multiple sensors with high sampling rate reveal considerable shortages in the analysis…

Anomaly detection aims at identification of suspicious items, observations or events by differing from most of the data. Intrusion Detection, Fault Detection, and Fraud Detection are some of the various applications of Anomaly Detection. The Machine learning classifier algorithms used in these applications would greatly affect the overall efficiency. This work is an extension of…

This paper is an extension of work originally presented in conference name. The goal is to propose new fault detection and fault isolation techniques for a polytypic linear parameter-varying system (LPV). In this work, an adaptive observer design is formulated for a given polyquadratic Lyapunov function. Subsequently, new sufficient conditions are given in terms of…

This paper focuses on studying the problem of fault tolerant control (FTC), including a detailed fault detection and diagnosis (FDD) module using observer banks which consists of output and unknown input observers applied to a continuous stirred tank reactor (CSTR). The main objective of this paper is to use a FDD module here proposed to…

The angle of attack is a critical flight parameter for commercial aviation aircraft, because automatic envelope protection systems rely on it to keep the aircraft within its safe flight envelope. Faulty measurements of the angle of attack could have catastrophic effects, leading to aircraft loss of control in flight and fatalities, as demonstrated by the…

The objective of this paper is to investigate the use of the 1-D wavelet analysis to extract several patterns from signals data sets collected from healthy and faulty input-output signals of control systems as a preliminary step in real-time implementation of fault detection diagnosis and isolation strategies. The 1-D wavelet analysis proved that is an…

This paper extends some of our research results disseminated in the most recent awarded international conference paper concerning the implementation in real time of a sliding mode observer state estimator. For the same case study developed in the conference paper, more precisely a DC servomotor angular speed control system, we extend the proposed concept of…