A New Induction Motor Adaptive Robust Vector Control based on Backstepping

In this paper, a novel approach to nonlinear control of induction machine, recursive on-line estimation of rotor time constant and load torque are developed. The proposed strategy combines Integrated Backstepping and Indirect Field Oriented Controls. The proposed approach is used to design controllers for the rotor flux and speed, estimate the values of rotor time constant and load torque and track their changes on-line. An open loop estimator is used to estimate the rotor flux. Simulation results are presented which demonstrate the effectiveness of the control technique and on-line estimation

A PI/Backstepping Approach for Induction Motor Drives Robust Control

International audienceThis paper presents a robust control design procedure for induction motor drives in case of modeling errors and unknown load torque. The control law is based on the combination of nonlinear PI controllers and a backstepping methodology. More precisely, the controllers are determined by imposing flux-speed tracking in two steps and by using appropriate PI gains that are nonlinear functions of the system state. A comparative study between the proposed PI/Backstepping approach and the feedback linearizing control is made by realistic simulations including load torque changes, parameter variations and measurement noises. Flux-speed tracking results show the proposed method effectiveness in presence of strong disturbances

The neural network-based control system of direct current motor driver

This article aims to propose an adaptive control system for the direct current motor driver based on the neural network. The control system consists of two neural networks: the first neural network is used to estimate the speed of the direct current motor and the second neural network is used as a controller. The plant in this research includes motor and the driver circuit so it is a complex model. It is difficult to determine the exact parameters of the plant so it is difficult to build the controller. To solve the above difficulties, the author proposes an adaptive control system based on the neural network to control the plant reach the high quality in the case of unknowing the parameters of the plant. The results are that the control quality of the system is very good, the response speed always follows the desired speed and the transition time is small. The simulation results of the neural network control system are shown and compared with that of a PID controller to demonstrate the advantages of the proposed method

Artificial Neural Network-Based Gain-Scheduled State Feedback Speed Controller for Synchronous Reluctance Motor

This paper focuses on designing a gain-scheduled (G-S) state feedback controller (SFC) for synchronous reluctance motor (SynRM) speed control with non-linear inductance characteristics. The augmented model of the drive with additional state variables is introduced to assure precise control of selected state variables (i.e. angular speed and d-axis current). Optimal, non-constant coefficients of the controller are calculated using a linear-quadratic optimisation method. Non-constant coefficients are approximated using an artificial neural network (ANN) to assure superior accuracy and relatively low usage of resources during implementation. To the best of our knowledge, this is the first time when ANN-based gain-scheduled state feedback controller (G-S SFC) is applied for speed control of SynRM. Based on numerous simulation tests, including a comparison with a signum-based SFC, it is shown that the proposed solution assures good dynamical behaviour of SynRM drive and robustness against q-axis inductance, the moment of inertia and viscous friction fluctuations

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

Model reference adaptive backstepping control of double star induction machine with extended Kalman sensorless control

Introduction. Newly, the design of a controller for speed control of double star induction motor as a research focus. Consequently, backstepping technique is used to recursively construct a stable control law for speed and flux. Nevertheless, this control law coming from backstepping requires the knowledge of speed and flux values; in practice the measurement sensors are expensive and fragile. The novelty of this work consists to propose a control strategy which based on accurate Kalman filter observer that estimates speed, flux and torque. This extended Kalman filter is an optimal state estimator and is usually applied to a dynamic system that involves a random noise environment. Purpose. Apply a backstepping control of double star induction motor based on principle of rotor flux orientation. This approach consists in finding a Lyapunov function that allows deducing a control law and a modified adaptation rule is referred and sufficient conditions for the stability of the command-observer, in contrast to other techniques who use nonlinear principle. Results. The simulation results are shown to illustrate the performance of the proposed scheme under parametric uncertainties by simulation on MATLAB. The obtained results showed the robustness of the sensorless control in front of load and parameters variation of double stator induction motor. The research directions of the model were determined for the subsequent implementation of results with simulation samples.Вступ. Новітня розробка контролера для регулювання швидкості асинхронного двигуна з подвійною зіркою є предметом дослідження. Отже, метод відступу використовується для рекурсивної побудови стабільного закону керування швидкістю та потоком. Тим не менш, цей закон керування, що випливає з відступу, вимагає знання значення швидкості та потоку; на практиці вимірювальні датчики коштовні та недовговічні. Новизна даної роботи полягає в тому, щоб запропонувати стратегію управління на основі точного спостерігача за фільтром Калмана, який оцінює швидкість, потік і крутний момент. Цей розширений фільтр Калмана є оптимальним засобом оцінки стану і зазвичай застосовується до динамічної системи, яка включає середовище випадкових шумів. Мета. Застосування підходу відступу до керування асинхронним двигуном з подвійною зіркою на основі принципу орієнтації потоку ротора. Цей підхід полягає у знаходженні функції Ляпунова, яка дозволяє вивести закон керування та модифіковане правило адаптації, а також достатні умови для стабільності спостерігача команд, на відміну від інших методик, які використовують нелінійний принцип. Результати. Результати моделювання наведені для ілюстрації роботи запропонованої схеми за параметричних невизначеностей шляхом моделювання на MATLAB. Отримані результати показали надійність безсенсорного керування перед зміною навантаження та параметрів асинхронного двигуна з подвійним статором. Визначені напрямки дослідження моделі для подальшої реалізації результатів на прикладах моделювання