A kernel method computes Koopman eigenfunctions that preserve the Jacobian spectrum for Lyapunov-based stability analysis of nonlinear dynamical systems.
Khalil,Nonlinear systems
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A neural network learns port-Hamiltonian dynamics without forcing the Hamiltonian to be convex and preserves stability at multiple equilibria instead of only one.
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RKHS method for computing Koopman-based Lyapunov functions
A kernel method computes Koopman eigenfunctions that preserve the Jacobian spectrum for Lyapunov-based stability analysis of nonlinear dynamical systems.
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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.