A kernel-based framework with a representer theorem reduces identification of nonlinear port-Hamiltonian systems to a finite-dimensional non-convex problem solved by a convergent algorithm.
Numerical methods to compute a minimal realization of a port-Hamiltonian system
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abstract
Port-Hamiltonian (pH) systems are a very important modeling tool in almost all areas of systems and control, in particular in network based model of multi-physics multi-scale systems. They lead to remarkably robust models that can be easily interconnected. This paper discusses the derivation of pH models from time-domain input-output data. While a direct construction of pH models is still an open problem, we present three different indirect numerical methods for the realization of pH systems. The algorithms are implemented in MATLAB and their performance is illustrated via several numerical examples.
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math.OC 1years
2026 1verdicts
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Kernel-based identification of nonlinear port-Hamiltonian systems
A kernel-based framework with a representer theorem reduces identification of nonlinear port-Hamiltonian systems to a finite-dimensional non-convex problem solved by a convergent algorithm.