integrated fuzzylogic controller for a brushless dc servomotor system

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Integrated fuzzy logic controller for a Brushless DC Servomotor system Ehab Al Hamayel Abdullah Abo Daqqah Supervised by Dr. Mohammad Al Janaideh

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This presentation discusses the designing and simulation of "Integrated fuzzy logic controller for a Brushless DC Servomotor system" using Matlab simulink

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Page 1: Integrated fuzzylogic controller for a Brushless DC Servomotor system

Integrated fuzzylogic controller for a

Brushless DC Servomotor system

Ehab Al Hamayel Abdullah Abo Daqqah Supervised by Dr. Mohammad Al Janaideh

Page 2: Integrated fuzzylogic controller for a Brushless DC Servomotor system

Outlines• Abstract

• Problem description.

• The Mathematical Model Of the system.

• The control system.

• Conclusion

Keywords: BLDC: Brushless DC servomotor FLC: Fuzzy logic controller IFLC: Integrated fuzzy logic controller

Page 3: Integrated fuzzylogic controller for a Brushless DC Servomotor system

Abstract

• The proposed controller systems consist of two -input fuzzy integrated fuzzy logic controller (IFLC) for rotation speed control of brushless dc servomotor drive.

• The input for the controller are error e(t), and change in error (first derivative of error ce(t)) with a single-output.

• The IFLC is designed using FLC and proportional derivation integral (PID) controllers.

Page 4: Integrated fuzzylogic controller for a Brushless DC Servomotor system

• The brushless dc motors (BLDC) are used in various applications such as defense, industries, robotics, etc. In these applications, the motor should be precisely controlled to give the desired performance.

• BLDC motors are relatively easy to control, and considered to be high performance motor that is capable of providing large amounts of torque over a vast speed range.

• The Torque vs. speed curve is shown in figure.1

Problem description

Page 5: Integrated fuzzylogic controller for a Brushless DC Servomotor system

BLDC Motor Torque-Speed characteristics curve

Page 6: Integrated fuzzylogic controller for a Brushless DC Servomotor system

The physical system structure

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The mathematical modelThe voltage equation of motor can be described by

The electromagnetic torque is linearly proportional to the armature current and the equation is given by:

The load torque

And the motion equation can be expressed as:

Page 9: Integrated fuzzylogic controller for a Brushless DC Servomotor system
Page 10: Integrated fuzzylogic controller for a Brushless DC Servomotor system

The transfer function parameters

Page 11: Integrated fuzzylogic controller for a Brushless DC Servomotor system

The Block Diagram and the unity feedback response

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PID controller design

S-C: Kp=2.124, Ki=29.104 C-C: Kp=0.567, Ki=2845.865

Page 14: Integrated fuzzylogic controller for a Brushless DC Servomotor system

PID Time response

Page 15: Integrated fuzzylogic controller for a Brushless DC Servomotor system

Increasing Friction and inertia

Page 16: Integrated fuzzylogic controller for a Brushless DC Servomotor system

FLC Controller

Cd k= 1*10^(-14), Cd k1= 1000, Sat=[-6000, 6000] (optimal response)

Page 17: Integrated fuzzylogic controller for a Brushless DC Servomotor system

FLC Inputs fuzzy sets and Rules using Sugeno-type reasoning and Matlab Anfis tool box

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FLC Controller response

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IFLC Controller

Cd k= 1*10^(-14), Sat=[-1000, 1000], C-S: Kp= 30, KI= 88.107, Kd=1.00 C-C: Kp=1.00, Ki= 350.941 (optimal response)

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IFLC Time response

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Conclusion• The design and development of two-input FLC and IFLC for the

speed control of brushless DC servomotor is being developed. • Simulation results indicate that the IFLC provides the best

performance in comparison with PID and conventional FLC.

• By several further tuning attempts, we got a better responses for both CFLC and IFLC as shown below:

Page 26: Integrated fuzzylogic controller for a Brushless DC Servomotor system

CFLC Response after several tuning attempts

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IFLC Response after several tuning attempts

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• The present system can further be improved by adding one more input variable (change of change of error cce). With three-input IFLC will get superior, more robust, faster, flexible, cost-effective, insensitive to the parameter variations control system , but it will require more computational time, so it’s necessary to use more powerful processing unit.

Page 31: Integrated fuzzylogic controller for a Brushless DC Servomotor system

THANK YOU