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Performance of Networked DC Motor with Fuzzy Logic Controller  [PDF]
B. Sharmila,N. Devarajan
International Journal of Computer Science Issues , 2010,
Abstract: In the recent years the usage of data networks has been increased due to its cost effective and flexible applications. A shared data network can effectively reduce complicated wiring connections, installation and maintenance for connecting a complex control system with various sensors, actuators, and controllers as a networked control system. For the time-sensitive application with networked control system the remote dc motor actuation control has been chosen. Due to time-varying network traffic demands and disturbances, the guarantee of transmitting signals without any delays or data losses plays a vital role for the performances in using networked control systems. This paper proposes Fuzzy Logic Controller methodology in the networked dc motor control and the results are compared with the performance of the system with Ziegler-Nichols Tuned Proportional-Integral-Derivative Controller and Fuzzy Modulated Proportional-Integral-Derivative Controller. Simulations results are presented to demonstrate the proposed schemes in a closed loop control. The effective results show that the performance of networked control dc motor is improved by using Fuzzy Logic Controller than the other controllers.
International Journal of Engineering Science and Technology , 2011,
Abstract: This paper presents Hybrid fuzzy logic controller (HFLC) for the well developed and sophisticated simulation model of Brush less DC (BLDC) motor drive using MATLAB. The developed simulation model has been examined by the PID controller and HFLC. The performance of the controllers is evaluated more precisely from various simulation studies for variations in the load torque and speed of BLDC motor drive. A performance comparison of two controllers is also carried out by taking various performance measures such as settling time, steady state error, peak overshoot, the integral of the absolute value of the error (IAE) and the integral of the time-weighted squared error (ITSE). The results confirm that the developed simulation model is very convenient for the precise evaluation of performance and the HFLC shows improved performance over the PID controller in terms of disturbance rejection or parameter variation.
Fuzzy PID Controllers Using FPGA Technique for Real Time DC Motor Speed Control  [PDF]
Basil Hamed, Moayed Almobaied
Intelligent Control and Automation (ICA) , 2011, DOI: 10.4236/ica.2011.23028
Abstract: The design of intelligent control systems has become an area of intense research interest. The development of an effective methodology for the design of such control systems undoubtedly requires the synthesis of many concepts from artificial intelligence. The most commonly used controller in the industry field is the proportional-plus-integral-plus-derivative (PID) controller. Fuzzy logic controller (FLC) provides an alternative to PID controller, especially when the available system models are inexact or unavailable. Also rapid advances in digital technologies have given designers the option of implementing controllers using Field Programmable Gate Array (FPGA) which depends on parallel programming. This method has many advantages over classical microprocessors. In this research, A model of the fuzzy PID control system is implemented in real time with a Xilinx FPGA (Spartan-3A, Xilinx Company, 2007). It is introduced to maintain a constant speed to when the load varies.,The model of a DC motor is considered as a second order system with load variation as a an example for complex model systems. For comparison purpose, two widely used controllers “PID and Fuzzy” have been implemented in the same FPGA card to examine the performance of the proposed system. These controllers have been tested using Matlab/Simulink program under speed and load variation conditions. The controllers were implemented to run the motor as real time application under speed and load variation conditions and showed the superiority of Fuzzy-PID.
A Comparative Analysis of Controllers Controlling Uncertainty in the Form of 2nd Order Load, Affecting the Robust Position Control of DC Motor  [PDF]
Er. Farhad Aslam,Birendra Kumar Yadav,Ram Sharan Choudhary,Gopal Kumar Choudhary
International Journal of Soft Computing & Engineering , 2013,
Abstract: All the industrial process applications requirerobust position control of DC motor. The aim of this paper is todesign a robust position control of DC motor by selectingdifferent controllers like P, PI, PID and their tuning methods.The model of a DC motor is considered as a third order systemwith incorporating uncertainty. This paper compares thedifferent kinds of tuning methods of parameter for PIDcontroller. One is the controller design by Zeigler and Nicholsmethod, second is the auto tuning of the controller in basicdesign mode and third is in the extended design mode. It wasfound that the proposed PID parameters adjustment in the basicand extended design mode is far better than the P, PI and Zeiglerand Nichols method. The proposed method could be applied tothe higher order system also.
Design and Implementation of Fuzzy Position Control System for Tracking Applications and Performance Comparison with Conventional PID
Nader Jamali Soufi Amlashi
IAES International Journal of Artificial Intelligence (IJ-AI) , 2012, DOI: 10.11591/ij-ai.v1i1.409
Abstract: This paper was written to demonstrate importance of a fuzzy logic controller in act over conventional methods with the help of an experimental model. Also, an efficient simulation model for fuzzy logic controlled DC motor drives using Matlab/Simulink is presented. The design and real-time implementation on a microcontroller presented. The scope of this paper is to apply direct digital control technique in position control system. Two types of controller namely PID and fuzzy logic controller will be used to control the output response. The performance of the designed fuzzy and classic PID position controllers for DC motor is compared and investigated. Digital signal Microcontroller ATMega16 is also tested to control the position of DC motor. Finally, the result shows that the fuzzy logic approach has minimum overshoot, and minimum transient and steady state parameters, which shows the more effectiveness and efficiency of FLC than conventional PID model to control the position of the motor. Conventional controllers have poorer performances due to the non-linear features of DC motors like saturation and friction.
Adaptive Fuzzy Logic Controllers for DC Drives: A Survey of the State of the art
E. E. El-kholy,A. M. Dabroom,Adel E. El-kholy
Journal of Electrical Systems , 2006,
Abstract: Fuzzy Logic Control (FLC) has gained a great demand in process control applications. Fuzzy Logic (FL) technology enables the use of engineering experience and experimental results in designing an expert system capable of handling uncertain or fuzzy quantities. This paper presents a comprehensive review of FLC in the field of Direct Current (DC) motor drive systems. Firstly, the principles of fuzzy logic theory will be briefly presented. Secondly, the employment of the FL techniques in a control system will be outlined. The concept of FLC can be extended for application to different DC motor drives such as: series, separately, shunt and permanent magnet DC motor. The limitations of FLC when applied to DC motor drives have been widely reported in the literature. This article also cites these limitations as well as the advancements in solving them through, for example, the genetic algorithms and the neural networks techniques.
Fuzzy-Logic Based Speed Control of Induction Motor Considering Core Loss into Account  [PDF]
Mohammad Abdul Mannan, Asif Islam, Mohammad Nasir Uddin, Mohammad Kamrul Hassan, Toshiaki Murata, Junji Tamura
Intelligent Control and Automation (ICA) , 2012, DOI: 10.4236/ica.2012.33026
Abstract: Rotor flux and torque of an induction motor (IM) are decoupled to obtain performance of DC motor. The decoupling strategy has been developed in terms of stator current components where the core loss is neglected. Many different controllers including fuzzy logic controller (FLC) with neglecting core loss have been designed to control the speed of induction motor. The outcome of investigation about the effect of core loss on indirect field oriented control (IFOC) has been concluded that the actual flux and torque are not reached to the reference flux and torque if core loss is neglected. Thus, the purpose of this paper is to propose a fuzzy logic speed controller of induction motor where flux and torque decoupling strategy is decoupled in terms of magnetizing current instead of stator current to alleviate the effects of core loss. The performances of proposed fuzzy-logic-based controller have been verified by computer simulation. The simulation of speed control of IM using PI and FLC are performed. The simulation study for high-performance control of IM drive shows the superiority of the proposed fuzzy logic controller over the conventional PI controller.
Speed control of brushless DC motor by using fuzzy logic PI controller  [PDF]
M. V. Ramesh,J. Amarnath,S. Kamakshaiah,G. S. Rao
Journal of Engineering and Applied Sciences , 2011,
Abstract: This paper presents the fuzzy, PI controller for speed control of BLDC motor. The controller uses three fuzzy logic controllers and three PI controllers. The output of the PI controllers is summed and is given as the input to the current controller. The current controller uses P controller. The mathematical modeling of BLDC motor is also presented. The BLDC motor is fed from the inverter where the rotor position and current controller is the input. The fuzzy logic control is learned continuously and gradually becomes the main effective control. The Simulink software was used to simulate the proposed scheme. The results are obtained for variable load torque.
Cherifi DJ,Miloud Y
Journal of Current Research in Science , 2013,
Abstract: This paper presents a control method with fuzzy logic controller to regulate the speed of an induction motor. The performances of the fuzzy logic controller are compared with a sliding mode controller. Both controllers are implemented using a testing bench and a simple cassy card. The experiment results are very satisfactory.
Design A Hybrid Intelligent Controller (Fuzzy-Based Ant Colony Algorithm) For Improving A Tracking Performance of Actual Output Response of SEDC Motor Under The Effect of External Disturbances
Ahmad M.El-Fallah Ismail, Rajiv Ranjan Tewari
International Journal of Electrical, Electronics and Data Communication , 2013, DOI: irajijeedc12
Abstract: For electrical drives good dynamic performance is mandatory so as to respond to the changes in command speed and torques, so various speed control techniques are being used for real time applications. The speed of a DC motor can be controlled using various controllers like PID Controller, Fuzzy Logic Controller, Ant Colony Algorithm (ACA) and Hybrid Fuzzy-ACA Controller. Fuzzy-ACA Controller is recently getting increasing emphasis in process control applications. The paper describes application of Hybrid Fuzzy-ACA Controller in an enhancement of stability and accuracy of the SEDC Motor under the effect of the external disturbances and noise that is implemented in MATLAB/SIMULINK. The simulation study indicates the superiority Hybrid Fuzzy-ACA Controller over the Ant Colony Algorithm (ACA) and fuzzy logic controller separately. This control seems to have a lot of promise in the applications of power electronics. The speed of theSEDC motor can be adjusted to a great extent so as to provide easy control and high performance. There are several conventional and numeric types of controllers intended for controlling the SEDC motor speed and executing various tasks: PID Controller, Fuzzy Logic Controller; or the combination between them: Fuzzy-Swarm, Fuzzy-Neural Networks, FuzzyGenetic Algorithm, Fuzzy-Ants Colony, Fuzzy-Particle Swarm Optimization. We describe in this paper the use of Ant Colony Algorithm (ACA) for designing an optimal fuzzy logic controller of a SEDC Motor. In this case, our approach will optimize the membership functions of a fuzzy logic controller (FLC) using ACA and the obtained results were simulated on Matlab environment. Excellent flexibility and adaptability as well as high precision and good robustness are obtained by the proposed strategy
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