Hysteresis behavior of smart materials, raw materials in multi-physical systems, confuses the conventional numerical methods and comes over their knowledge in real-time studies. Artificial intelligence (AI) is introduced to bypass the problem. The AI potential gets well the non-linearity behavior of the smart material systems and performs the real-time simulation. In this work, the smart system is an antagonistic system of two-shape memory alloy wires (AS SMA) that plays an actuator role and achieves the butterfly behavior shape. Multiple Neural Networks (NN) are studied and performed to model the pseudo-elasticity behavior of AS SMA. Besides modeling, control of the AS SMA is a core study to invest this system in various smart applications. Reinforcement learning, the non-supervised strategy, is used to control the non-linearity of AS SMA as well. Subsequently, the AI design and the AI control can perform the smart device actuated by AS SMA.
About Rodayna Hdeme
As I a passionate about Innovation and Mechanism, my journey started with a Master's degree in Fundamental Physics that transformed into a Master's degree in Robotic-Mechanical engineering. With a mechanical and theoretical mentality, my passion pushes me deeply into Artificial Intelligence (AI) to innovate multi-physical systems using Smart Materials. My Ph.D. footprints can prove the potential of AI in multidisciplinary. My efforts started in a robotic and actuators environment and improved into medical applications. My research sat out at the "Lebanese University faculty of science" in Lebanon to SIGMA CLERMONT Engineer's School in France, then at Université Clermont Auvergne (UCA) doctoral school, and currently at CiTIUS laboratory in Spain as a scientific collaboration to add more value to my thesis and chase more achievements. It is my ambition to work on my thesis and put all my skills and knowledge acquired during my academic and professional experiences to be fully developed in the artificial intelligence, mechanics, and material science fields.