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

Speed Control of Induction Motor using Fuzzy Logic approach

This thesis presents a methodology for implementation of a rule-based fuzzy logic controller applied to a closed loop Volts/Hz induction motor speed control. The Induction motor is modeled using a dq axis theory. The designed Fuzzy Logic Controller’s performance is weighed against with that of a PI controller. The pros of the Fuzzy Logic Controllers (FLCs) over the conventional controllers are: (i) they are economically advantageous to develop, (ii) a wider range of operating conditions can be covered using FLCs, and (iii) they are easier to adapt in terms of natural language. Another advantage is that, an initial approximate set of fuzzy rules can be impulsively refined by a self-organizing fuzzy controller. For V/f speed control of the induction motor, a reference speed has been used and the control architecture includes some rules. These rules portray a nonchalant relationship between two inputs and an output, all of which are nothing but normalized voltages. These are: The input speed error denoted by Error (e). The input derivative of speed error denoted by Change of error (∆e), and The output frequency denoted by Change of Control (ω_sl). The errors are evaluated according to the rules in accordance to the defined member functions. The member functions and the rules have been defined using the FIS editor given in MATLAB. Based on the rules the surface view of the control has been recorded. The system has been simulated in MATLAB/SIMULINK® and the results have been attached. The results obtained by using a conventional PI controller and the designed Fuzzy Logic Controller has been studied and compared. The controller has then been tuned by trial and error method and simulations have been run using the tuned controller. Keywords : V/f induction motor speed control, dq axis theory, Fuzzy Logic controller, Mamdani Architecture

Maximum Torque per Ampere Control of Permanent Magnet Synchronous Motor Using Genetic Algorithm

 Permanent magnet synchronous motor (PMSM) drives have many advantages over other drives, i.e. high efficiency and high power density. Particularly, PMSMs are epoch-making and are intensively studied among researchers, scientists and engineers. This paper deals with a novel high performance controller based on genetic algorithm. The scheme allows the motor to be driven with maximum torque per ampere characteristic. In this paper assuming an appropriate fitness function, the optimum values for d-axis current of motor set points at each time are found and then applied to the controller. Simulation results show the successful operation of the proposed controller

New trends in electrical vehicle powertrains

The electric vehicle and plug-in hybrid electric vehicle play a fundamental role in the forthcoming new paradigms of mobility and energy models. The electrification of the transport sector would lead to advantages in terms of energy efficiency and reduction of greenhouse gas emissions, but would also be a great opportunity for the introduction of renewable sources in the electricity sector. The chapters in this book show a diversity of current and new developments in the electrification of the transport sector seen from the electric vehicle point of view: first, the related technologies with design, control and supervision, second, the powertrain electric motor efficiency and reliability and, third, the deployment issues regarding renewable sources integration and charging facilities. This is precisely the purpose of this book, that is, to contribute to the literature about current research and development activities related to new trends in electric vehicle power trains.Peer ReviewedPostprint (author's final draft

Fuzzy-PID Controller for Azimuth Position Control of Deep Space Antenna

The Deep Space Antennas are essential in achieving communication over very large distances. However, the pointing accuracy of this antenna needs to be as precise as possible to enable effective communication with the satellite. Therefore, this work addressed the pointing accuracy for a Deep Space Antenna using Fuzzy-PID control technique by improving the performance objectives (settling time, percentage overshoot rise time and mainly steady-state error) of the system. In this work, the PID controller for the system was first of all designed and simulated after which, a fuzzy controller was also designed and simulated using MATLAB and Simulink respectively for the sake of comparison with the fuzzy-PID controller. Then, the fuzzy-PID controller for the system was also designed and simulated using MATLAB and Simulink and it gives a better performance objective (rise time of 1.0057s, settling time of 1.6019s, percentage overshoot of 1.8013, and steady-state error of 2.195e-6) over the PID and fuzzy controllers respectively. Therefore, the steady state error shows improved pointing accuracy of 2.195e-6

MODELING AND SIMULATION OF PM MOTOR TESTING ENVIRONMENT TOWARDS EV APPLICATION CONSIDERING ROAD CONDITIONS

The electric vehicle (EV) performance testing is an indispensable aspect of the design study and marketing of electric vehicle. The development of a suitable electric motor testing environment for EVs is very significant. On the one hand, it provides a relatively realistic testing environment for the study of the key technologies of electric vehicles, and it also plays an essential role in finding a reasonable and reliable optimization scheme. On the other hand, it provides a reference to the evaluation criteria for the products on the market. This thesis is based on such requirements to model and simulate the PM motor testing environment towards EV applications considering road conditions. Firstly, the requirements of the electric motor drive as a propulsion system for EV applications are investigated by comparing to that of the traditional engine as a propulsion system. Then, as the studying objective of this work, the mathematical model of PMSM is discussed according to three different coordinate systems, and the control strategy for EV application is developed. In order to test the PM motor in the context of an EV, a specific target vehicle model is needed as the virtual load of the tested motor with the dyno system to emulate the real operating environment of the vehicle. A slippery road is one of the severe driving conditions for EVs and should be considered during the traction motor testing process. Fuzzy logic based wheel slip control is adopted in this thesis to evaluate the PM motor performance under slippery road conditions. Through the proposed testing environment, the PM motor can be tested in virtual vehicle driving conditions, which is significant for improving the PM motor design and control

Analisis Bibliometrik Riset PID Speed Control pada Rentang 2013-2022

Penelitian ini bertujuan untuk memberikan gambaran terkait perkembangan riset PID speed control dalam satu dekade terakhir (2013-2022). Metode yang digunakan dalam artikel ini adalah analisis bibliometrik dengan menggunakan VOSviewer, Tableau Public dan Rstudio Biblioshiny. Database yang digunakan adalah Scopus. Dengan kata kunci pencarian “PI* speed control*”, diperoleh 258 dokumen publikasi yang terdiri dari 105 artikel jurnal dan 153 artikel prosiding yang menjadi dataset utama yang digunakan dalam artikel ini. Dari hasil analisis terlihat bahwa jumlah publikasi riset PID speed control berfluktuasi setiap tahunnya. Top 10 dokumen dengan jumlah sitasi terbanyak juga dibahas dalam artikel ini. Author paling produktif dan author paling berpengaruh dalam riset PID speed control terungkap yaitu Verma, A dan Choi, H.H. Topik yang sedang tren dan menjadi hotspot dalam riset PID speed control adalah particle swarm optimization, direct torque control, extended Kalman filter, current predictive control, sliding mode control, model predictive control dan disturbance observer. Akhirnya, artikel ini dapat memberikan informasi yang bermanfaat bagi para peneliti empiris untuk menentukan kebaruan dan research gap untuk penelitian selanjutnya dalam tema utama PID speed control

Multi Objective Optimization Using Non-Dominated Sorting Approach For Load Frequency Control

This work provides an in-depth analysis on the implementation of multi objective optimization based on non-dominated sorting for load frequency control by using proportional-integral-derivative (PID) controller for interconnected reheat thermal power system. The load frequency control is use to control the frequency and inter-area (tie line) oscillation. When the load demand slightly changes, the frequency of the system will be affected and the control action need be react as soon as possible to prevent system instability. The real power is related with frequency which will slightly change due to any changing in frequency. The two area power system model will be considered in this investigation. The optimization technique which has been implemented is the Evolutionary Programming (EP). The weighted sum approach of EP is considered in order to provide multiple solution point by varying the weighted. The non-dominated point has been selected to optimize the PID gains to provide least overshoot value and fast frequency response of the system. Two objectives function will be considered for this investigation and has been characterized by the performance criterions which are Integral of Time Multiplied Absolute Error (ITAE) and Integral of Time Weighted Squared Error (ITSE). Optimum PID parameters which able to provide the best performance in terms of lower settling time and less overshoot value in the frequency deviation response will be determined

A Fast Induction Motor Speed Estimation based on Hybrid Particle Swarm Optimization (HPSO)

AbstractIntelligent control and estimation of power electronic systems by fuzzy logic and neural network techniques with fast torque and flux show tremendous promise in future. This paper proposed the application of Hybrid Particle Swarm Optimization (HPSO) for losses and operating cost minimization control in the induction motor drives. The main advantages of the proposed technique are; its simple structure and its straightforward maximization of induction motor efficiency and its operating cost for a given load torque. As will be demonstrated, Hybrid Particle Swarm Optimization (HPSO) is so efficient in finding the optimum operating machine's flux level. The results demonstrate the good quality and robustness in the system dynamic response and reduction in the steady-state and transient motor ripple torque