Abstract:
Benefits of the AC motor over the DC motor and steady increase in industrial standards and
automation where speed of rotation is of primary concern and its exercising control over its speed
is the necessity has led to the development of various control strategies to efficiently control the
speed of an AC motor. To implement the various control strategies, an efficient power modulator
would be needed which could provide the necessary power to AC motor as desired by the control
strategy.
The power modulators are expected to ensure they provide the power to the motor as desired as
well as improve the quality of the power it takes from the grid. An overview of AC-AC regulators
is done with emphasis on Matrix converters. Matrix converters and their various topologies are
studied and simulated with.
For the induction motor controlling to achieve variable speed, Vector Control (VC) or Field
Oriented Control (FOC) have become the industrial standard. The vector control technique
decouples the two component of stator current: one is responsible for controlling torque and other
is controlling flux independently as in the case of separately excited fully compensated DC motor.
Artificial Neural Networks or ANNs have been of special interest in the recent times, with their
ability to learn instead of being programmed coupled with inherent ability to carry out parallel
processing of data. This means they can fit highly non-linear functions and do calculations fast
making them ideal tool in the control of induction motor drive. A novel neural controller has been
studied which able to do slip calculations and matrix rotations in the original field oriented control
of motor. A through study of the steps involved in the process is done along with simulations.
The analysis has been carried out on the basis of result obtained by numerical simulations. The
simulation and evaluation of matrix converter and the neural network controller is performed using
a fed three phase squirrel cage induction motor for a 2HP rating.
