Hyeong-Joon Ahn

Physics-Informed Ideal Acceleration Control with PIV-Parallel Sliding-Mode Learning for a Linear Motor Motion Stage

A physics-informed learning framework that explicitly separates stabilization from learning is proposed, in which closed-loop stability is guaranteed a priori by a PIV–SMC architecture, while a radial basis function (RBF) neural network learns only the residual open-loop acceleration required to realize the prescribed...