ABSTRACT
Fuzzy
logic control has become an important methodology in control engineering. The
paper proposes a Fuzzy Logic Controller (FLC) for controlling a speed of SRM
drive. The objective of this work is to compare the operation of P& PI
based conventional controller and Artificial Intelligence (AI) based fuzzy
logic controller to highlight the performances of the effective controller. The
present work concentrates on the design of a fuzzy logic controller for SRM speed
control. The result of applying fuzzy logic controller to a SRM drive gives the
best performance and high robustness than a conventional P & PI controller.
Simulation is carried out using Matlab/Simulink.
KEYWORDS: P Controller, PI
Controller, Fuzzy Logic Controller, Switched Reluctance Motor
SOFTWARE: MATLAB/SIMULINK
BLOCK
DIAGRAM
Figure 1. Block
diagram of SRM speed control
SIMULATION
MODELS
Figure 2. Simulation
model using P controller
Figure 3. Simulation
model using PI controller.
Figure 4. Simulink
model using FLC.
SIMULATION RESULTS
Figure 5. Output flux.
Figure 6. Output current
Figure 7. Output torque.
Figure 8. Speed.
CONCLUSION
Thus
the SRM dynamic performance is forecasted and by using MATLAB/simulink the
model is simulated. SRM has been designed and implemented for its speed control
by using P, PI controller and AI based fuzzy logic controller. We can conclude
from the simulation results that when compared with P & PI controller, the fuzzy
Logic Controller meet the required output. This paper presents a fuzzy logic
controller to ensure excellent reference tracking of switched reluctance motor drives.
The fuzzy logic controller gives a perfect speed tracking without overshoot and
enchances the speed regulation. The SRM response when controlled by FLC is more
advantaged than the conventional P& PI controller.
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