In this study, a new model‐based fault detection and isolation (FDI) strategy is proposed for field‐oriented control (FOC) induction motor (IM) drives. Actuator faults are addressed, and specifically, single open‐circuit faults are considered in this study. The residual signals are synthesised by taking the resulting closed‐loop dynamics when a FOC strategy is applied, that is, the residuals are referenced to the synchronous reference frame ( dq ^e ‐coordinates), which are generated by using a bank of variable structure observers to obtain a robust FDI scheme. Thus, subsystems sensitive to a specific fault, but decoupled from other faults are obtained in a natural way, where only two stator currents and the mechanical position are required for fault isolation purposes. Residual evaluation is carried out in the stator reference frame ( dq ‐coordinates) for the IM model, where the residual direction (angle) is employed to isolate a fault in each one of the six power switches in a voltage source inverter. In addition, the observer FDI scheme can be combined with a fault re‐configuration strategy in order to improve the reliability of the motor drive. Experimental results are illustrated for a three‐phase 3/4 HP IM drive at different reference frequencies and load torques with single open‐circuit faults that verify the ideas presented in this work.

Switch semiconductors are essential components in power electronics stages for photovoltaic (PV) systems, which are prone to failures caused mainly by thermal stress, thereby affecting PV energy production. Specifically, dc/dc boost power converters are commonly used as maximum power point tracking (MPPT) systems. Several works have been reported so far in the literature for switch fault detection and isolation (FDI) purposes in boost power converters. However, most of them require additional sensors and circuitry to those included in any PV system, which generate extra costs on the overall system. Hence, this work presents an efficient and low-cost switch fault diagnosis proposal, which requires only the most common measurements in PV systems, namely, PV current and voltage. This work departs from a data-driven FDI methodology for diagnosing switch open- and short-circuit faults in dc/dc boost converters. The experimental results have been evaluated against sudden irradiance changes and switch faults in a test bench of 350 $\text {W}$ operating under a closed-loop nonlinear control action for MPPT purposes by using the dSpace 1104 board.

This paper proposes a fault identification system for short and open-circuit switch faults (SOCSF) for a dc/dc converter acting as a Maximum Power Point Tracker (MPPT) in Photovoltaic (PV) systems. A closed-loop operation is assumed for the boost dc/dc converter. A linearizing control plus a Proportional-Derivative (PD) controller is suggested for PV voltage regulation at the maximum power point (MPP). In this study, the SOCSF are modeled by using an additive fault representation and the fault identification (FI) system is synthesized departing from a Luenberger observer. Hence, an FI signal is obtained, which is insensitive to irradiance and load current changes, but affected by the SOCSF. For FI purposes, only the sensors used in the control system are needed. Finally, an experimental evaluation is presented by using a solar array simulator dc power supply and a boost dc/dc converter of 175 $\mathrm{W}$ in order to validate the ideas this study exposes.

Distributed maximum power point tracking photovoltaic (PV) systems based on series-connected dc/dc converters are one of the most promising PV configurations for an enhanced security and efficiency in distributed generation systems. Most of the works reported so far in the literature for control and stability analysis of these configurations are based on small-signal ac models. This could be a significant limitation, as this kind of linearization produces a good approximation of the nonlinear model of series-connected dc/dc converters only at the operating point. However, PV systems must be controlled for a large set of operating points with a satisfactory performance and robustness. Moreover, stability analysis of series-connected dc/dc converters has not yet been widely discussed in previous research. Therefore, this article presents a nonlinear model of series-connected boost dc/dc converters and develops control and stability analysis to fill the gap in this emerging topic. A systematic experimental and numerical investigation is performed in order to validate the effectiveness of the proposed control approach in this study.

Open‐ and short‐circuit faults (OSCFs) in boost dc–dc converters for photovoltaic (PV) maximum power point trackers (MPPTs) imply an inefficiency after fault is triggered, which affect the security and profitability of PV projects. Hence, fault detection and isolation (FDI) techniques have become an important issue for PV technology. In this study, a model‐based FDI technique is proposed to boost dc–dc converters in PV MPPT systems. As is well‐known, major issues of model‐based FDI techniques have always been parametric uncertainty and no‐modelled dynamics. This study focuses on how to mitigate these shortcomings by applying a high‐gain observer (HGO) as a residual generator. A striking feature of HGO's is that exponential stability is still guaranteed for bounded disturbances (or faults). As demonstrated in this study, under an integral control action in the closed‐loop control system, OSCFs are characterised for ever‐growing signals, enabling the suggested FDI scheme. Also, the FDI proposal is decoupled from PV current (irradiance changes) and load variations, thereby avoiding false alarms. Moreover, the output‐injection gain and thresholds are selected such that the fault diagnosis is achieved in eight switching cycles, enabling a fast and reliable diagnosis. Experimental results are illustrated to validate the FDI scheme proposed in this study.