A comparative study of conventional PID and fuzzy-PID for DC motor speed control
Self Tuning Fuzzy PID and proportional-integral-derivative (PID) controllers are developed and compared for used in direct current (DC) motor. A simulation study of both controller for the armature voltage controlled DC motors is performed to overcome the appearrance of nonlinearities and uncerta...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6625/1/24p%20AHMAD%20MUHYIDDIN%20YUSOF.pdf http://eprints.uthm.edu.my/6625/2/AHMAD%20MUHYIDDIN%20YUSOF%20WATERMARK.pdf http://eprints.uthm.edu.my/6625/ |
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| Summary: | Self Tuning Fuzzy PID and proportional-integral-derivative (PID) controllers are
developed and compared for used in direct current (DC) motor. A simulation study
of both controller for the armature voltage controlled DC motors is performed to
overcome the appearrance of nonlinearities and uncertainties in the system. The
fuzzy logic controller is designed according to fuzzy rules so that the systems are
fundamentally robust. There are 49 fuzzy rules for self tuning of each parameter of
FUZZY-PID controller. Fuzzy Logic is used to tune each parameter of the
proportional, integral and derivative (KP,KI,KD) gains of the PID controller. The FLC
has two inputs. One is the motor speed error between the reference and actual speed
and the second is changed in speed error (rate of change error). The output of the
FLC i.e the parameter of PID controller are used to control the speed of the DC
motor [1]. Different types of membership functions such as triangular, trapezoidal,
gaussian are evaluated in the fuzzy control and the best performance will be used in
FUZZY PID for comparative analysis with the conventional PID. The membership
function and the rules have been defined using FIS editor given in MATLAB. Three
different scenario are simulated, which are step response, load disturbances and noise
disturbance. The FUZZY-PID controller has been tuned by trial and error and
performance parameters are Rise time, Settling Time, Percent Overshoot and Integral
Absolute error [21]. |
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