International Journal of Mechatronics and Manufacturing Technology ISSN: 3139-5058 (Online)

Authors: Ravi Kumar , Nirmal Sachdeva

Abstract: Recent advances in artificial intelligence (AI) have significantly impacted control strategies in mechatronic devices. Traditional control systems, though effective, often struggle to manage the complexity and uncertainty in modern devices. AI-based control systems, including machine learning (ML) and deep learning (DL) techniques, provide adaptive, robust, and predictive capabilities that enhance system performance. This paper presents a comprehensive review of AI-enhanced control strategies for mechatronic devices, including neural network-based controllers, fuzzy logic systems, reinforcement learning, and hybrid approaches. Benefits, challenges, and applications across robotics, precision manufacturing, and autonomous systems are discussed. The study concludes with a perspective on future trends and research directions in AIdriven mechatronic control.

Keywords: AI control, Mechatronic systems, Neural networks, Fuzzy logic, Reinforcement learning, Adaptive control, Robotics