01-06-2012, 01:43 PM
Induction Motor Speed Control using Fuzzy Logic Controller
Induction Motor Speed Control using Fuzzy Logic Controller.pdf (Size: 478.2 KB / Downloads: 244)
INTRODUCTION
AC Induction motors are being applied today to a wider
range of applications requiring variable speed. Generally,
variable speed drives for Induction Motor (IM) require both
wide operating range of speed and fast torque response,
regardless of load variations. This leads to more advanced
control methods to meet the real demand. The conventional
control methods have the following difficulties
1. It depends on the accuracy of the mathematical model
of the systems
2. The expected performance is not met due to the load
disturbance, motor saturation and thermal variations
3. Classical linear control shows good performance only
at one operating speed
4. The coefficients must be chosen properly for
acceptable results, whereas choosing the proper
coefficient with varying parameters like set point is
very difficult
To implement conventional control, the model of the
controlled system must be known. The usual method of
computation of mathematical model of a system is difficult.
When there are system parameter variations or environmental
disturbance, the behavior of the system is not satisfactory.
Usually classical control is used in electrical motor drives. The
classical controller designed for high performance increases
the complexity of the design and hence the cost.
VARIOUS CONTROL TECHNIQUES
Due to advances in power electronic switches and
microprocessors, variable speed drive system using various
control technique have been widely used in many applications,
namely Field oriented control or vector control, Direct torque
control, Sensorless vector control.
Field Oriented Control
Field oriented control (FOC) technique is intended to
control the motor flux, and thereby be able to decompose the
AC motor current into “flux producing” and “torque
producing” components. These current components can be
treated separately, and then recombined to create the actual
motor phase currents. This gives a solution to the boost
adjustment problem, and also provides much better control of
the motor torque, which allows higher dynamic performance.
BLOCK DIAGRAM OF INDUCTION MOTOR
In order to accomplish field oriented control, the controller
needs to have an accurate “model” of the motor. Over the last
several years a large number of different schemes have been
proposed to accomplish the “flux and torque control” desired.
Many of the today’s technique involve some sort of selftuning
at startup in order to obtain information which helps to
design accurate model of the motor to produce more optimal
control. In addition, there are also techniques by which the
models can adaptively adjust to changing conditions such as
the motor temperature going from cold to warm which will
have an impact of slip.
IMPLEMENTATION OF FUZZY LOGIC CONTROLLER
To obtain fuzzy based model of the motor, the training
system derives information from two main sources,
a. The static flux linkage curves of the motor, which
provides important information about the electromagnetic
characteristics of the motor
b. The dynamic real time operating waveforms of the
motor, which can include real-time operating effects,
such as mutual coupling between phases, temperature
variations, eddy currents and skin effects.
During the training phase, each input-output data pair,
which consists of a crisp numerical value of measured flux
linkage, current, angle and voltage is used to generate the
fuzzy rules.
CONCLUSION
The proposed speed controller gives maximum torque over
the entire speed range. In the steady state, the efficiency of the
induction motor is increased. The validity of the proposed
controller is confirmed through the simulation results. To
implement it in the laboratory various parameters like rotor
flux, rotor current and operating points, rotor parameter tuning
are to be estimated. The proposed speed control system can be
useful for the variable speed drive system.