Artificial Intelligence Based Speed Control of Brushless DC Motor
Thread Rating:
  • 0 Vote(s) - 0 Average
  • 1
  • 2
  • 3
  • 4
  • 5
seminar surveyer
Active In SP
**

Posts: 3,541
Joined: Sep 2010
#1
20-01-2011, 03:15 PM




K.Naga Sujatha, Dr.K.Vaisakh and Anand.G

Abstract
This paper presents a control scheme combined with neural network, fuzzy controller and PI- controller for the brushless DC motor. The neural network control learned continuously and gradually becomes the main effective control. Performances of the proposed neural network are compared with the corresponding fuzzy PI controller and conventional PI controller. Matlab/simulink software was used to simulate the proposed scheme. Neural network improves speed response and also reduces torque ripples. The simulation results are verified with new control strategy.


INTRODUCTION
ermanent magnet Brushless DC (BLDC) motors are becoming very popular rapidly in industries such as

automotive, aerospace, consumer, medical, industrial automation equipment and instrumentation because of their high efficiency, high power factor, silent operation, compact form, reliability, and low maintenance.

The speed regulators are conventional PI controllers in order to achieve high performance drive. The unexpected change in load conditions or environmental factors would produce overshoot, oscillation of the motor speed, oscillation of the torque, long settling time and causes deterioration of drive performance. In view of improvement in speed response during start up, an abrupt change in command torque and reduction in torque ripple, a kind of neural network which adjusts control rule according to inputs of neural network is presented. Sometimes NN are proved to be more efficient and their performance is less sensitive to parametric variations than conventional controllers. With the learning ability of neural network, neural networks have widely been recognized as a powerful tool in industrial control, commercial prediction, and image processing applications etc. Many authors havehinted the neural networks as powerful building blocks for a wide class of complex nonlinear system control strategies.


For more


Reply

Important Note..!

If you are not satisfied with above reply ,..Please

ASK HERE

So that we will collect data for you and will made reply to the request....OR try below "QUICK REPLY" box to add a reply to this page

Quick Reply
Message
Type your reply to this message here.


Image Verification
Please enter the text contained within the image into the text box below it. This process is used to prevent automated spam bots.
Image Verification
(case insensitive)

Possibly Related Threads...
Thread Author Replies Views Last Post
  MULTI-LEVEL INVERTER CAPABLE OF POWER FACTOR CONTROL WITH DC LINK SWITCHES PPT study tips 2 625 06-09-2016, 10:04 AM
Last Post: Dhanabhagya
  Presentation On Project Automatic Traffic Light Control System ppt study tips 1 778 02-04-2016, 02:28 PM
Last Post: mkaasees
  Bluetooth Enabled Mobile Phone Remote Control for PC PPT seminar flower 2 2,367 05-08-2015, 11:13 PM
Last Post: Guest
  WEATHER MONITORING AND INSTRUMENT CONTROL SYSTEM USING MICROCONTROLLER project report tiger 6 7,097 04-10-2014, 08:55 PM
Last Post: OsKFAHX
  MICROCONTROLLER BASED DAM GATE CONTROL SYSTEM full report seminar class 13 10,321 13-07-2014, 11:33 PM
Last Post: Guest
  Real –Time DC Servo Motor Position Control by PID Controllers Using Labview project girl 3 1,180 20-05-2014, 03:46 PM
Last Post: lucia9901
  Control of Voltage Source Inverters using PWM/SVPWM for Adjustable Speed Drive project girl 2 1,359 15-03-2014, 03:30 PM
Last Post: seminar project topic
  PLC BASED TRAFFIC CONTROL SYSTEM full report seminar class 5 10,708 10-01-2014, 03:08 PM
Last Post: seminar project topic
  SPEED CONTROL OF DC MOTOR USING PWM TECHNIQUE seminar class 10 24,876 19-10-2013, 07:29 PM
Last Post: Guest
  FPGA IMPLEMENTATION OF HIGH SPEED CONVOLUTION AND DECONVOLUTION seminar flower 1 1,031 11-10-2013, 01:45 PM
Last Post: Guest