Deep Reinforcement Learning Controller for 3D Path-following and Collision Avoidance by Autonomous Underwater Vehicles

Control theory provides engineers with a multitude of tools to design controllers that manipulate the closed-loop behavior and stability of dynamical systems. These methods rely heavily on insights into the…

HAM for next generation of digital twins

Highlight: The team of Suraj Pawar and Shady Ahmed wins the best paper award for this work at the Deep Wind 2021 COnference The physics-based modeling has been the workhorse…

Digital Twin: Values, Challenges and Enablers From a Modeling Perspective

Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances…