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arXiv · 2112.12999

Total Energy Shaping with Neural Interconnection and Damping Assignment -- Passivity Based Control

Santiago Sanchez-Escalonilla·Rodolfo Reyes-Baez·Bayu Jayawardhana
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Abstract

In this work we exploit the universal approximation property of Neural Networks (NNs) to design interconnection and damping assignment (IDA) passivity-based control (PBC) schemes for fully-actuated mechanical systems in the port-Hamiltonian (pH) framework. To that end, we transform the IDA-PBC method into a supervised learning problem that solves the partial differential matching equations, and fulfills equilibrium assignment and Lyapunov stability conditions. A main consequence of this, is that the output of the learning algorithm has a clear control-theoretic interpretation in terms of passivity and Lyapunov stability. The proposed control design methodology is validated for mechanical systems of one and two degrees-of-freedom via numerical simulations.

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Santiago Sanchez-Escalonilla, Rodolfo Reyes-Baez, Bayu Jayawardhana. 2021-12-24. Total Energy Shaping with Neural Interconnection and Damping Assignment -- Passivity Based Control. https://arxiv.org/abs/2112.12999

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