الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
This thesis focuses on the application of metaheuristic optimization
techniques for fractional-order control in nonlinear systems. The research
investigates the effectiveness of optimal fractional-order controllers
compared to conventional controllers, with a particular emphasis on two
different systems: path tracking of mobile robots and maximum power
point tracking in various load scenarios.
For path tracking of mobile robots, two case studies are conducted
involving both holonomic and nonholonomic robots. The performance of
optimal fractional-order controllers is evaluated against conventional
controllers. The results demonstrate the superiority of optimal fractional-
order controllers in terms of accuracy, and robustness in achieving precise
path tracking for both types of robots.
In the context of maximum power point tracking, three case studies
are carried out, considering resistive, DC, and AC dynamic loads. Optimal
fractional-order controllers are compared to conventional controllers in
terms of tracking the maximum power point under various load
conditions. The findings reveal the significant advantages of using optimal
fractional-order controllers, including enhanced tracking accuracy,
improved response time, and increased overall system efficiency.
Moreover, the thesis highlights the benefits of employing
metaheuristic optimization techniques in the design and tuning of
fractional-order controllers. These techniques provide a systematic and
efficient approach to finding optimal controller parameters, considering
the complex and nonlinear nature of the systems under study. The results
demonstrate that metaheuristic optimization methods effectively optimize
the performance of fractional-order controllers, leading to superior
system behaviour and improved control outcomes.