Abstract
In the intricate landscapes of modern control systems, traditional methods often struggle with complex dynamics, uncertain environments, and changing operational demands. This is where computational intelligence (CI) steps in, revolutionizing the field with its powerful algorithms and adaptive capabilities. This article delves into the multifaceted integration of CI techniques in control systems, exploring their diverse applications, advantages, and ongoing challenges. From neural networks and fuzzy logic to evolutionary algorithms and swarm intelligence, CI empowers control systems to learn, adapt, and optimize performance in a dynamic and data-rich world.