A neural network learns port-Hamiltonian dynamics without forcing the Hamiltonian to be convex and preserves stability at multiple equilibria instead of only one.
Hamiltonian dynamics learning from point cloud observations for nonholonomic mobile robot control
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Structure- and Stability-Preserving Learning of Port-Hamiltonian Systems
A neural network learns port-Hamiltonian dynamics without forcing the Hamiltonian to be convex and preserves stability at multiple equilibria instead of only one.