dc.contributor.advisor |
Ghosh, Prof. Dr. Bashudeb Chandra |
|
dc.contributor.author |
Hossen, Md. Belal |
|
dc.date.accessioned |
2019-09-29T06:55:21Z |
|
dc.date.available |
2019-09-29T06:55:21Z |
|
dc.date.copyright |
2019 |
|
dc.date.issued |
2019-06 |
|
dc.identifier.other |
ID 1303554 |
|
dc.identifier.uri |
http://hdl.handle.net/20.500.12228/536 |
|
dc.description |
This thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, June 2019. |
en_US |
dc.description |
Cataloged from PDF Version of Thesis. |
|
dc.description |
Includes bibliographical references (pages 113-117). |
|
dc.description.abstract |
Permanent Magnet Brushless DC (PMBLDC) Motor Drive is familiar as an innovative
research for their compact size, silent operation, reliability, high efficiency, simple
construction, easy to control and less maintenance requirements. Design cost of PMBLDC
motor drive has been reduced drastically due to the invention of rare earth magnetic
materials and advancement of power semiconductor devices. The semiconductor power
devices are turned on or off sequentially using triggering and commutation circuits. Based
on the rotor position the controller generates requisite signals to control the operation of
the power inverter. A high performance controller is required to obtain desired
performance of the drive system. It is noticed that PMBLDC Motor has a complexity to
handle multi variable and nonlinear system. The motor speed control is frequently needed
for controlling various drives such as robotics, copters, electric vehicles and other drives of
applications. The high performance drives require very fast response, high efficiency and
parameter insensitive. It is not possible to achieve desired performance with conventional
PI controller. Tuning of controller parameters is necessary to achieve desired performance.
To overcome these problems this study proposes the following controllers (1) Single
Neuron based Adaptive (SNA) Controller, (2) Single Neuron based Adaptive PID
(SNAPID) Controller, (3) Adaptive Neuro Fuzzy Inference System (ANFIS) based
Controller with Radial Basis Function (RBF), (4) ANFIS Controller based on Takagi-
Sugeno Model, (5) ANFIS Controller based on Line Voltage Model and (6) Wavelet
Neural Network (WNN) based Controller. A PI controller with constant parameter is also
designed and it is tuned by Ziegler- Nichols method. Each controller was simulated by
developing software in C++ environment and performance of each controller is compared
with PI controller. To get better speed, torque and current responses field orientation
control method and square wave reference current input to the machine are considered with
the above controllers. In this process, direct axis current is considered to zero and
quadrature axis current produces useful torque. The drive performance was tested under
different operating conditions such as constant starting condition, sudden load torque
changes, speed variation and parameter changes. All proposed controllers perform well
under speed variation and constant starting condition except fixed PI and WNN based
controller. It is also observed that their speed responses are fast. For suddenly increment of
load torque, motor speed is fallen by WNN based Controller, fixed PI and SNAPID Controller but SNA Controller, ANFIS Controller based on Takagi-Sugeno Model, ANFIS
controller based on Line Voltage Model and ANFIS Controller with RBF perform well
with constant speed. Finally, it is seen that all controllers with PMBLDC Motor drive work
effectively without any performance degradation in the increment of stator resistance
hence, the proposed controllers perform as insensitive controller with the variation of stator
resistance. |
en_US |
dc.description.statementofresponsibility |
Md. Belal Hossen |
|
dc.format.extent |
119 pages |
|
dc.language.iso |
en_US |
en_US |
dc.publisher |
Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh |
en_US |
dc.rights |
Khulna University of Engineering & Technology (KUET) thesis/dissertation/internship reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. |
|
dc.subject |
Permanent Magnet Brushless DC (PMBLDC) Motor drives |
en_US |
dc.subject |
Single Neuron based Adaptive (SNA) |
en_US |
dc.subject |
Single Neuron based Adaptive PID (SNAPID) |
en_US |
dc.subject |
Adaptive Neuro Fuzzy Inference System (ANFIS) |
en_US |
dc.subject |
Wavelet Neural Network (WNN) |
en_US |
dc.title |
Performance Analysis of Single Neuron Adaptive PID, WNN and ANFIS Type Controller Based PMBLDC Motor Drive |
en_US |
dc.type |
Thesis |
en_US |
dc.description.degree |
Master of Science in Electrical and Electronic Engineering |
|
dc.contributor.department |
Department of Electrical and Electronic Engineering |
|