Induction motor (IM) drives, specifically the three-phase IMs, are a nonlinear system that are difficult to explain theoretically because of their sudden changes in load or speed conditions. Thus, an advanced controller is needed to enhance IM performance. Among numerous control techniques, fuzzy logic controller (FLC) has increasing popularity in designing complex IM control system due to their simplicity and adaptability. However, the performance of FLCs depends on rules and membership functions (MFs), which are determined by a trial-and-error procedure. The main objective of this paper is to present a critical review on the control and optimization techniques for solving the problems and enhancing the performance of IM drives. A detailed study on the control of variable speed drive, such as scalar and vector, is investigated. The scalar control functions of speed and V/f control are explained in an open- and closed-loop IM drive. The operation, advantages, and limitations of the direct and indirect field-oriented controls of vector control are also demonstrated in controlling the IM drive. A comprehensive review of the different types of optimization techniques for IM drive applications is highlighted. The rigorous review indicates that existing optimization algorithms in conventional controller and FLC can be used for IM drive. However, some problems still exist in achieving the best MF and suitable parameters for IM drive control. The objective of this review also highlights several factors, challenges, and problems of the conventional controller and FLC of the IM drive. Accordingly, the review provides some suggestions on the optimized control for the research and development of future IM drives. All the highlighted insights and recommendations of this review will hopefully lead to increasing efforts toward the development of advanced IM drive controllers for future applications.

Optimization techniques to enhance the performance of induction motor drives: A review

Power electronics contribution to renewable energy conversion addressing emission reduction: Applications, issues, and recommendations

A state-of-the-art techno-economic review of distributed and embedded energy storage for energy systems

Torque control for induction motors under the scheme of indirect field-oriented control (IFOC) considering rotor resistance perturbations is analyzed via linear approximations. Several important characteristics of IFOC are elucidated, leading to the design of linear, robust, and performance-based torque, speed, and position controllers. In particular, the resulting controllers are of a low order, robust to rotor resistance perturbations, and are designed according to classical performance specifications, which is a combination of characteristics that have been historically difficult to achieve. General control design guidelines valid for any induction motor are presented. In addition, the stability and minimum phase conditions of the IFOC torque controller are fully derived for any induction motor. These conditions are of prime importance when designing fixed linear speed or position controllers. A case study for a typical motor, including the design of a series of robust controllers and real-time experimental results, is presented. The proposed approach makes use of well-known classical control methods that allow the results presented here to be further extended using any linear single-input-single-output controller design tool, such as H∞ and quantitative feedback theory.

Speed and Position Controllers Using Indirect Field-Oriented Control: A Classical Control Approach

In this research study, a model reference adaptive system (MRAS) speed estimator for speed sensorless direct torque and flux control (DTFC) of an induction motor drive (IMD) using two adaptation mechanism schemes are proposed to replace the conventional proportional integral controller (PIC). The first adaptation mechanism scheme is based on Type-1 fuzzy logic controller (T1FLC), which is used to achieve high performance sensorless drive in both transient as well as steady state conditions. However, the Type-1 fuzzy sets are certain and unable to work effectively when higher degree of uncertainties presents in the system which can be caused by sudden change in speed or different load disturbances, process noise etc. Therefore, a new Type-2 fuzzy logic controller (T2FLC) based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties and improves the performance and also robust to various load torque and sudden change in speed conditions, respectively. The detailed performances of various adaptation mechanism schemes are carried out in a MATLAB/Simulink environment with a speed sensor and speed sensorless modes of operation when an IMD is operating under different operating conditions, such as, no-load, load and sudden change in speed, respectively. To validate the different control approaches, the system also implemented on real-time system and adequate results are reported for its validation.

Type-2 fuzzy logic control based MRAS speed estimator for speed sensorless direct torque and flux control of an induction motor drive.

A novel scheme for current sensor faults diagnosis in the stator of a DFIG described by a T-S fuzzy model

The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor.

Implementation of a new fuzzy vector control of induction motor.

Integrating the Internet of Things (IoT) technology in solar photovoltaic (PV) systems is considered as an important aspect for monitoring, supervising and performances evaluation. The main aim of this work is to design a low-cost monitoring system for the maximum power point tracking (MPPT) in a PV system. Two electronics board have been developed: a data-acquisition sensing and a DC-DC boost converter. The designed monitoring board consists of an embedded board (Arduino Mega 2560 based upon ATmega2560), current and voltage sensors, voltage regulator Mini BEC, LCD Display, and a WiFi module ESP8266 to transmit the monitored data ( $I_{PV}, V_{PV}, V_{L}, I_{L}$ and $D$ ) on the internet. In addition, a website has been also designed to store and display the monitored data in real time. The designed prototype has been verified experimentally at Renewable Energy Laboratory (REL) of Jijel University, Algeria. Based on the monitored data the users can check easily if the system works well or not by just comparing the measured output power with the one expected by a model.

A low-cost monitoring system for maximum power point of a photovoltaic system using IoT technique

Fault-tolerant controller (FTC) designs for doubly fed induction generators (DFIGs) with actuator faults have recently gained considerable attention due to their important role in maintaining the safety and reliability of DFIG-based wind turbines via configured redundancy. The objective of this paper is to propose a novel active fault-tolerant tracking control strategy for a DFIG subject to actuator faults. The proposed strategy consists of first designing a proportional integral observer (PIO) for simultaneous system states and fault estimation and then secondly the FTC, which depends on the estimated states and faults. The objective of such a controller is to drive the state of the system to track a reference state generated by a reference fault-free model (nominal system). In addition, the main results for stability are demonstrated through a quadratic Lyapunov function, formulated in terms of linear matrix inequalities (LMIs) in order to guarantee the stability of the whole closed-loop system and to reduce the actuator fault effects with noise attenuation. Furthermore, the gain matrices of the FTC and the PIO are computed by solving a set of LMIs using the YALMIP toolbox with the SeDuMi solver. Finally, the simulation results under constant and time-varying actuator faults are provided to show the effectiveness of the developed FTC scheme.

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An advanced robust fault-tolerant tracking control for a doubly fed induction generator with actuator faults

The aims of this work, is the survey of the design and application of speed and flux sliding mode controllers for vector control of an induction motor powered by a solar photovoltaic energy. The solar photovoltaic energy nowadays, is one of the renewable energies sources present in various domains of applications. Moreover, the photovoltaic generator (GPV) output voltage depends of several climatic factors, such as the irradiations and the temperature. To overcome these problems, one (...)

/pdf/a-sliding-mode-control-associated-to-the-field-oriented-5airtl5s5n.pdf

L. Barazane

Papers

A novel scheme for current sensor faults diagnosis in the stator of a DFIG described by a T-S fuzzy model

Implementation of a new fuzzy vector control of induction motor.

A low-cost monitoring system for maximum power point of a photovoltaic system using IoT technique

An advanced robust fault-tolerant tracking control for a doubly fed induction generator with actuator faults

A sliding mode control associated to the field-oriented control of asynchronous motor supplied by photovoltaic solar energy