PSO BASED TAKAGI-SUGENO FUZZY PID CONTROLLER DESIGN FOR SPEED CONTROL OF PERMANENT MAGNET SYNCHRONOUS MOTOR

A permanent magnet synchronous motor (PMSM) is one kind of popular motor. They are utilized in industrial applications because their abilities included operation at a constant speed, no need for an excitation current, no rotor losses, and small size. In the following paper, a fuzzy evolutionary algorithm is combined with a proportional-integral-derivative (PID) controller to control the speed of a PMSM. In this structure, to overcome the PMSM challenges, including nonlinear nature, cross-coupling, air gap flux, and cogging torque in operation, a Takagi-Sugeno fuzzy logic-PID (TSFL-PID) controller is designed. Additionally, the particle swarm optimization (PSO) algorithm is developed to optimize the membership functions' parameters and rule bases of the fuzzy logic PID controller. For evaluating the proposed controller's performance, the genetic algorithm (GA), as another evolutionary algorithm, is incorporated into the fuzzy PID controller. The results of the speed control of PMSM are compared. The obtained results demonstrate that although both controllers have excellent performance; however, the PSO based TSFL-PID controller indicates more superiority

Modeling and Linearization of DFIG Based Wind Turbine

Usage level of wind units in power systems is increasing rapidly. There are different kinds of wind turbine generator. The Doubly-Fed Induction Generator (DFIG), is one of the most widely used electrical machines in the megawatt-class wind turbines. In a DFIG-based wind turbine, the stator is connected to grid directly while the rotor is connected a back-to-back converter via slip rings. Current sensor fault diagnosis for renewable power of wind turbine based on DFIG has gained serious importance. In this work, mathematical modeling of DFIG is presented. Nonlinear state equations are linearized with Takagi-Sugeno (T-S) Local Models for current sensor fault diagnosis. Modelling error between linear and nonlinear model is minimized by heuristic approach on membership functions. A bank of observer-based residual generator system for fault diagnosis is created, so additive and gain faults of stator current sensors can be detected and isolated

Upravljanje otporno na kvarove asinkronog motora zasnovano na deskriptorskom observeru

This paper presents an active Fault Tolerant Control (FTC) strategy for induction motor (IM) that ensures Field Oriented Control (FOC) and offset the effect of the sensor faults despite of the load torque disturbance. The proposed approach uses a fuzzy descriptor approach to estimate simultaneously the system state and the sensor fault. The physical model of IM is approximated by the Takagi-Sugeno (T-S) fuzzy technique in the synchronous d-q rotating frame with field-oriented control strategy. The stability conditions are analyzed using Lyapunov theory. The controller and observers gains are calculated by solving a set of Linear Matrix Inequalities (LMIs). Finally, the effectiveness of the proposed strategy have been illustrated in simulation and experimental results.U ovom radu je predstavljena strategija upravljanja otpornog na kvarove za asinkroni motor koja omogućuje vektorsko upravljanje bez pogreške uslijed kvara senzora i postojećeg poremećaja momenta tereta. Predloženi pristup koristi neizraziti deskriptor za estimaciju stanja sustava i kvara senzora. Fizikalni model asinkronog motora s vektorskim upravljanjem aproksimiran je korištenjem Takagi-Sugeno modela u rotirajućem d-q koordinatnom sustavu. Uvjeti stabilnosti analizirani us korištenjem Ljapunovljeve teorije. Konstante pojačanja regulatora i obzervera su izračunati rješavanjem skupa linearnih matričnih nejednadžbi. Učinkovitost predložene strategije je ilustrirana simulacijskim i eksperimentalnim rezultatima

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering

Soft Computing Techniques and Their Applications in Intel-ligent Industrial Control Systems: A Survey

Soft computing involves a series of methods that are compatible with imprecise information and complex human cognition. In the face of industrial control problems, soft computing techniques show strong intelligence, robustness and cost-effectiveness. This study dedicates to providing a survey on soft computing techniques and their applications in industrial control systems. The methodologies of soft computing are mainly classified in terms of fuzzy logic, neural computing, and genetic algorithms. The challenges surrounding modern industrial control systems are summarized based on the difficulties in information acquisition, the difficulties in modeling control rules, the difficulties in control system optimization, and the requirements for robustness. Then, this study reviews soft-computing-related achievements that have been developed to tackle these challenges. Afterwards, we present a retrospect of practical industrial control applications in the fields including transportation, intelligent machines, process industry as well as energy engineering. Finally, future research directions are discussed from different perspectives. This study demonstrates that soft computing methods can endow industry control processes with many merits, thus having great application potential. It is hoped that this survey can serve as a reference and provide convenience for scholars and practitioners in the fields of industrial control and computer science

Des nouvelles approches de commande et d’estimation non linéaires robustes dédiées aux entraînements électriques

The purpose of the research presented in this thesis is to propose a methodology for the control and observation of the induction motor (IM) based on the algorithms using the mean value theorem (MVT) and the transformation by sector non-linearity approach. In the first step, the different control techniques of electric drives were identified and analyzed. A robust state and estimation feedback control approach is then developed with variable parameters. In the field of low power, the removal of the mechanical speed sensor can be of economic interest and improve operational safety. We have presented two categories of methods that allow reconstructing and controlling the rotor speed with desired quantities under field-oriented control of the IM’s machine, the MVT observer and the robust MVT controller respectively. All the solutions have been validated by numerical simulation and affirmed by experimental tests to compare the accuracy and dynamics characteristics of the different methods with the MVT control. Finally, new robust control and estimation approaches with a novel representation for uncertain systems with varying parameters based on the MVT and sector nonlinear addressed to control the IM ‘s machine with FOC control. The results of the various simulation tests and the different experimental trials put into evidence the robustness and the success properties of the proposed algorithms. The thesis ends with a review of our contribution in terms of research

Fault Diagnosis and Fault Tolerant Control of Wind Turbines: An Overview

Wind turbines are playing an increasingly important role in renewable power generation. Their complex and large-scale structure, however, and operation in remote locations with harsh environmental conditions and highly variable stochastic loads make fault occurrence inevitable. Early detection and location of faults are vital for maintaining a high degree of availability and reducing maintenance costs. Hence, the deployment of algorithms capable of continuously monitoring and diagnosing potential faults and mitigating their effects before they evolve into failures is crucial. Fault diagnosis and fault tolerant control designs have been the subject of intensive research in the past decades. Significant progress has been made and several methods and control algorithms have been proposed in the literature. This paper provides an overview of the most recent fault diagnosis and fault tolerant control techniques for wind turbines. Following a brief discussion of the typical faults, the most commonly used model-based, data-driven and signal-based approaches are discussed. Passive and active fault tolerant control approaches are also highlighted and relevant publications are discussed. Future development tendencies in fault diagnosis and fault tolerant control of wind turbines are also briefly stated. The paper is written in a tutorial manner to provide a comprehensive overview of this research topic

Contribution à la commande des systèmes non linéaires : application à la machine synchrone à réluctance variable

N ombreux sont les problèmes en ingénierie nécessite l’estimation de l’état d’un système via un observateur. Cependant, la modélisation et la synthèse de l’observateur deviennent des taches difficiles pour des systèmes non linéaires. Face à ces difficultés, l’approche multimodèle peut être mise à profit. Les travaux de recherche présentés dans cette thèse portent sur l’estimation d’état des systèmes non linéaires représentés par des multimodèles flous de type Takagi-Sugeno couplé. Cette représentation est obtenue grâce à l’utilisation de la décomposition en secteurs non linéaire qui nous permettant de réécrire le nouveau système sous forme de polytopes sans perte d’information. Cette forme est ensuite utile pour la synthèse d’un observateur robuste vis-à-vis des entrées inconnues afin de reconstruire les états du système et les entrées inconnues. Après une brève introduction à l’approche multimodèle, le problème de l’estimation d’état des systèmes non linéaires décrits par les multimodèles flous couplés est abordé. Ensuite, nous présentons des algorithmes pour synthétiser des observateurs d’état robustes face à des entrées inconnues. Nous avons utilisé deux types d’observateurs à gains proportionnel-intégral et à gains multi-intégral. Finalement, nous appliquons ces approches au modèle d’une machine synchrone à réluctance variable

Advanced Fault-Tolerant Control of Induction-Motor Drives for EV/HEV Traction Applications: From Conventional to Modern and Intelligent Control Techniques

International audienceThis paper describes active fault-tolerant control systems for a high-performance induction-motor drive that propels an electrical vehicle (EV) or a hybrid one (HEV). The proposed systems adaptively reorganize themselves in the event of sensor loss or sensor recovery to sustain the best control performance, given the complement of remaining sensors. Moreover, the developed systems take into account the controller-transition smoothness, in terms of speed and torque transients. The two proposed fault-tolerant control strategies have been simulated on a 4-kW induction-motor drive, and speed and torque responses have been carried to evaluate the consistency and the performance of the proposed approaches. Simulation results, in terms of speed and torque responses, show the global effectiveness of the proposed approaches, particularly the one based on modern and intelligent control techniques in terms of speed and torque smoothness