الفهرس 
1.1.1 Review of Electric Motor DrivesOnly 14 pages are availabe for public view
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Abstract
Optimization is one of the most discussed topics in engineering and applied
research. The last decade has witnessed a great interest in using evolutionary
algorithms (EAs) such as genetic algorithms (GA) and Particle Swarm Optimization
(PSO), for multivariate optimization.
This thesis presents a modern approach of speed control for three-phase
induction motor (IM) using PSO algorithm to optimize the parameters of
Proportional-Integral (PI) and Hybrid Control (HC) which is a combination between PI
controller and Fuzzy Logic Controller (FLC). Also, comparison between different
controllers is achieved, using PI controller and HC which are tuned by two methods;
firstly a conventional fixed (Trial-and-Error) and secondly using PSO technique.
Hybrid of Fuzzy Logic (FL) and PI controller PSO-based for the speed control of given
motor is also performed to eliminate the drawbacks of PI speed controller
(overshoot, undershoot) and FLC (steady-state error). Also, The FLC is used to
overcome parameter variations, sudden speed or load changes and other non-linear
disturbances. A minimum number of fuzzy rules and membership functions (MFs) are
proposed in this thesis to reduce computational burden time as well as complexity.
This work employs also a technique called Field-Oriented Control (FOC) of IM to
achieve high performance of the drive.
Also, this thesis proposed a Gain-Scheduling Adaptive of a Proportional-
Integral (GSAPI) controller scheme for speed control of IM drives using a PSO
algorithm to optimize the PI parameters. The PI gains are allowed to vary within a
predetermined range and therefore, eliminate the problems faced by the
conventional fixed PI and the fixed PSO-PI without gain-scheduling control. The
performance of the GSAPI speed controller is simulated and compared with the
conventional fixed PI and fixed PSO-PI speed controllers under different operating
conditions.
A prototype of the proposed system is laboratory implemented and
controller is installed using a low cost digital signal processor (DSP 1104) in order to
approve the simulation results for different dynamic operating condition.