Port-Hamiltonian Neural Networks for Systems with Multiple Asymptotically Stable Equilibria
Standard port-Hamiltonian neural networks guarantee stability to only one equilibrium. This work introduces multiplicative Hamiltonian structures (ms-PHNNs) using a shared network to model systems with multiple stable equilibria, like the Duffing oscillator. It provides rigorous stability guarantees for these multi-attractor models.