dc.description.abstract |
Three phase induction motors have been widely used in many industrial applications.
e.g., on the electrical vehicle for creating traction process. The motor should be able to
track the reference to maintain the good output. Therefore, the speed controller should
be added to overcome this problem. However, conventional controllers have not been
successful for real time applications because of the change of reference and multiple
input multiple output and time variant parameters. Predictive techniques are best suited
for these situations. Model predictive control (MPC) is emerging as a powerful control
scheme for high performance control of induction motor (IM) drives due to its fast
speed response.
This thesis presents finite set models predictive speed control of indirect vector
controlled for a three-phase induction motor. The principle of vector control of
electrical drives is based on the control of both the magnitude and the phase of each
phase current and voltage. Indirect vector control to produce high performance in
induction Motor drives by decoupling rotor flux and torque producing current
components of stator current. The proposed system, complete mathematical model of
vector controlled induction motor with model predictive controller is described and
simulate in MATLAB for electrical vehicle system using squirrel cage type induction
motor. This paper explores that the finite set model predictive control technique tracks
the reference speeds with in 0.01sec and gives better performance than the proportional
integral (PI) speed controller. The results proved that the induction motor with the finite
set model predictive speed controller has superior transient response, and good
robustness in face of uncertainties including reference speed changes and load
disturbance. Moreover, accurate tracking performance has been achieved.
Keywords: AC Drives, Induction Motor, Model Predictive Control, Speed Sensorless,
Vector Controlled. |
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