Application of Intelligent Computing Techniques in Smart Electronic Control Systems

Abstract

Smart electronic control systems have evolved significantly with the integration of intelligent computing techniques such as artificial intelligence, machine learning, and adaptive algorithms. These techniques enhance system autonomy, accuracy, and efficiency in dynamic and complex operating environments. This paper explores the application of intelligent computing techniques in smart electronic control systems. It examines the role of intelligent algorithms in system modeling, control optimization, fault detection, and adaptive decision-making. The study highlights how intelligent control systems improve performance, reliability, and energy efficiency across applications including industrial automation, robotics, and smart infrastructure. The findings emphasize the growing importance of intelligent computing in the development of next-generation electronic control systems.