Comparison of DC Motor Speed Control Performance using Fuzzy Logic and Model Predictive Control Method PDF Download

Author: Mustefa Jibril
Publisher: GRIN Verlag
ISBN: 3346164152
Category : Computers
Languages : en
Pages : 6

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Book Description
Academic Paper from the year 2020 in the subject Computer Science - Miscellaneous, , language: English, abstract: The main target of this paper is to control the speed of DC motor by comparing the actual and the desired speed set point. The DC motor is designed using Fuzzy logic and MPC controllers. The comparison is made between the proposed controllers for the control target speed of the DC motor using square and white noise desired input signals with the help of Matlab/Simulink software. It has been realized that the design based on the fuzzy logic controller track the set pointwith the best steady state and transient system behavior than the design with MPC controller. Finally, the comparative simulation result prove the effectiveness of the DC motor with fuzzy logic controller.

Author: Khairul Afiq Zakaria
Publisher:
ISBN:
Category : Fuzzy logic
Languages : en
Pages : 61

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Book Description
The automatic control has played a vital role in the advance of engineering and science. Nowadays in industries, the control of direct current (DC) motor is a common practice thus the implementation of DC motor of controller speed is important. The main purpose of motor speed control is to keep the rotation of the motor at the present speed and to drive a system at the demand speed. The DC Series Wound Motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. The main purpose of this project is to control speed of DC Series Wound Motor using four controllers which are PID, PI, P, and Fuzzy Logic Controller (FLC). Initially all the controllers are developed by using MATLAB simulink model. In this project, PID, PI, and P controller are developed and tuned in order to get faster step response and the Fuzzy Logic Controller (FLC) is design based on the membership function and the rule base. The expectation of this project is the Fuzzy Logic Controller will get the best performance compared to other controllers in terms of settling time (Ts), rise time (Tr), peak time (Tp), and percent overshoot (%OS). Finally a GUI of these controllers are developed which allow the users to select any controller and change its parameters according to the different conditions under loaded and unloaded scenarios.

Author: Najiha Zulkifli
Publisher:
ISBN:
Category : Electric motors, Direct current
Languages : en
Pages : 216

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Book Description

Author: Ying Bai
Publisher: Springer Science & Business Media
ISBN: 1846284694
Category : Technology & Engineering
Languages : en
Pages : 342

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Book Description
This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers’ tuning processes and enhance the performance of their control systems. It further contains application examples.

Author: Marcian Cirstea
Publisher: Newnes
ISBN: 9780750655583
Category : Education
Languages : en
Pages : 416

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Book Description
*Introduces cutting-edge control systems to a wide readership of engineers and students *The first book on neuro-fuzzy control systems to take a practical, applications-based approach, backed up with worked examples and case studies *Learn to use VHDL in real-world applications Introducing cutting edge control systems through real-world applications Neural networks and fuzzy logic based systems offer a modern control solution to AC machines used in variable speed drives, enabling industry to save costs and increase efficiency by replacing expensive and high-maintenance DC motor systems. The use of fast micros has revolutionised the field with sensorless vector control and direct torque control. This book reflects recent research findings and acts as a useful guide to the new generation of control systems for a wide readership of advanced undergraduate and graduate students, as well as practising engineers. The authors guide readers quickly and concisely through the complex topics of neural networks, fuzzy logic, mathematical modelling of electrical machines, power systems control and VHDL design. Unlike the academic monographs that have previously been published on each of these subjects, this book combines them and is based round case studies of systems analysis, control strategies, design, simulation and implementation. The result is a guide to applied control systems design that will appeal equally to students and professional design engineers. The book can also be used as a unique VHDL design aid, based on real-world power engineering applications.

Author: Nur Azliza Ali
Publisher:
ISBN:
Category : Fuzzy logic
Languages : en
Pages : 84

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Book Description
The purpose of this project is to control the speed of DC motor by using fuzzy logic controller with MATLAB applications. The scopes includes the simulation and modeling of DC motor, implementation of fuzzy logic controller to actual DC motor and comparison between MATLAB simulation and experimental result. This research was about to introduce the new ability of estimating speed and control the DC motor. By using the controller, the speed can be tuned until it get similar to the desired output that user need. Data will be transferred from the controller to the DC motor using the DAQ card. Encoder will be used to detect speed error between the desired output and the measured output.

Author: S.N. Sivanandam
Publisher: Springer Science & Business Media
ISBN: 3540731903
Category : Technology & Engineering
Languages : en
Pages : 453

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Book Description
This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.

Author: Tushir Meena
Publisher: LAP Lambert Academic Publishing
ISBN: 9783659820731
Category :
Languages : en
Pages : 68

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Book Description
Fuzzy c-means (FCM) Clustering has been used to partition the input-output data and to determine the number of rules. By assuming Gaussian membership function for the premise parts, hybrid learning algorithm is used to update its parameters. This book presents a research work towards the development of a T-S fuzzy model for the speed control of dc motors. To be specific, an attempt is made to design a clustering based fuzzy logic controller for speed control of dc motors. The proposed approach provides a mechanism to obtain the reduced rule-set covering the whole input/output space as well as the parameters of membership functions for each input variable. The entire system has been modeled using MATLAB 7.0/Simulink toolbox.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 65

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Book Description

Author: Hiram Ponce-Espinosa
Publisher: Springer
ISBN: 3319024728
Category : Technology & Engineering
Languages : en
Pages : 232

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Book Description
This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: · approximation; · inference; · clustering; · control; · classification; and · audio-signal filtering. The text finishes with a consideration of directions in which AHNs could be implemented and developed in future. A complete LabVIEWTM toolkit, downloadable from the book’s page at springer.com enables readers to design and implement organic neural networks of their own. The novel approach to creating networks suitable for machine learning systems demonstrated in Artificial Organic Networks will be of interest to academic researchers and graduate students working in areas associated with computational intelligence, intelligent control, systems approximation and complex networks.