ABSTRACT:
Induction motor (IM) drives, specifically
the three-phase IMs, are a nonlinear system that are difficult to explain theoretically
because of their sudden changes in load or speed conditions. Thus, an advanced
controller is needed to enhance IM performance. Among numerous control
techniques, fuzzy logic controller (FLC) has increasing popularity in designing
complex IM control system due to their simplicity and adaptability. However, the
performance of FLCs depends on rules and membership functions (MFs), which are
determined by a trial and- error procedure. The main objective of this paper is
to present a critical review on the control and optimization techniques for
solving the problems and enhancing the performance of IM drives. A detailed
study on the control of variable speed drive, such as scalar and vector, is
investigated. The scalar control functions of speed and V/f control are
explained in an open- and closed-loop IM drive. The operation, advantages, and limitations
of the direct and indirect field-oriented controls of vector control are also
demonstrated in controlling the IM drive. A comprehensive review of the different
types of optimization techniques for IM drive applications is highlighted. The
rigorous review indicates that existing optimization algorithms in conventional
controller and FLC can be used for IM drive. However, some problems still exist
in achieving the best MF and suitable parameters for IM drive control. The
objective of this review also highlights several factors, challenges, and
problems of the conventional controller and FLC of the IM drive. Accordingly,
the review provides some suggestions on the optimized control for the research
and development of future IM drives. All the highlighted insights and
recommendations of this review will hopefully lead to increasing efforts toward
the development of advanced IM drive controllers for future applications.
KEYWORDS:
1. Induction
motor drive
2. Optimization
algorithms
3. Scalar
control
4. Vector
control
5. Fuzzy
logic controller
SOFTWARE: MATLAB/SIMULINK
BLOCK DIAGRAM:
Fig.
1. Architecture of the IM control system.
Fig.
2. Closed-loop of scalar control for IM drive.
BLOCK DIAGRAM OF DFOC FOR IM DRIVE
Fig.
3. Block diagram of DFOC for IM drive.
BLOCK DIAGRAM OF IFOC FOR IM DRIVE
Fig.
4. Block diagram of IFOC for IM drive.
Fig.5
Block diagram of DTC for IM drive
OPTIMIZATION TECHNIQUE BASED
ON PID SPEED CONTROLLER FOR SCALAR CONTROL
Fig.
6. Optimization technique based on PID speed controller for scalar control
OPTIMIZATION TECHNIQUE BASED ON PID CONTROLLERS FOR (A) DFOC AND (B)
IFOC
(a)
(b)
Fig.
7. Optimization technique based on PID controllers for (a) DFOC and (b) IFOC.
OPTIMIZATION TECHNIQUE BASED
ON FUZZY LOGIC SPEED CONTROLLER FOR SCALAR CONTROL.
Fig.
8. Optimization technique based on fuzzy logic speed controller for scalar
control.
OPTIMIZATION TECHNIQUE BASED ON FLC CONTROLLERS FOR (A) DFOC AND (B)
IFOC.
(a)
(b)
Fig.
9. Optimization technique based on FLC controllers for (a) DFOC and (b) IFOC.
CONCLUSION:
In this paper, an Indirect
Field-Oriented Control (IFOC) scheme for a drive system of three-phase
induction motor is effectively investigated and validated using various
simulation results in Matlab/Simulink. The performance of proposed controller
is verified by introducing variation in speed and load torque. Simulation
results demonstrate that PI has sluggish response compared to AFLC. In all load
torque variations, the proposed AFLC shows robustness and continues to track
the reference with small steady-state error. Moreover, AFLC based on LM is
robust to model parameter variations, load variations and less sensitive to
uncertainties and disturbances. The proposed scheme verifies superior and
smoother performance with improved dynamic response. Furthermore, the effectiveness of proposed
AFLC is evaluated and justified from performance indices IAE, ISE and ITAE.
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