5 papers
Physics-Informed Neural Networks with Learnable Loss Balancing and Transfer Learning
Reza Pirayeshshirazinezhad
We propose a self-supervised physics-informed neural network (PINN) framework that adaptively balances physics-based and data-driven supervision for scientific machine learning und…
Explainable AI-Enhanced Supervisory Control for Robust Multi-Agent Robotic Systems
Reza Pirayeshshirazinezhad, Nima Fathi
We present an explainable AI-enhanced supervisory control framework for multi-agent robotics that combines (i) a timed-automata supervisor for safe, auditable mode switching, (ii)…
Explainable AI-Enhanced Supervisory Control for High-Precision Spacecraft Formation
Reza Pirayeshshirazinezhad
We use artificial intelligence (AI) and supervisory adaptive control systems to plan and optimize the mission of precise spacecraft formation. Machine learning and robust control e…
SPINN: An Optimal Self-Supervised Physics-Informed Neural Network Framework
Reza Pirayeshshirazinezhad
A surrogate model is developed to predict the convective heat transfer coefficient of liquid sodium (Na) flow within rectangular miniature heat sinks. Initially, kernel-based machi…
Bicycle Stabilization using mechanism optimization and Digital LQR
Reza Pirayeshshirazinezhad
This study introduces lateral pendulum as an innovative balancer design for bicycle stabilization. This pendulum, operating in the bicycle's vertical plane, enables the bicycle to…