arXiv Open Access 2021

Data to Controller for Nonlinear Systems: An Approximate Solution

Johannes N. Hendriks James R. Z. Holdsworth Adrian G. Wills Thomas B. Schon Brett Ninness

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Abstrak

This paper considers the problem of determining an optimal control action based on observed data. We formulate the problem assuming that the system can be modelled by a nonlinear state-space model, but where the model parameters, state and future disturbances are not known and are treated as random variables. Central to our formulation is that the joint distribution of these unknown objects is conditioned on the observed data. Crucially, as new measurements become available, this joint distribution continues to evolve so that control decisions are made accounting for uncertainty as evidenced in the data. The resulting problem is intractable which we obviate by providing approximations that result in finite dimensional deterministic optimisation problems. The proposed approach is demonstrated in simulation on a nonlinear system.

Topik & Kata Kunci

math.OC eess.SY

Penulis (5)

Johannes N. Hendriks

James R. Z. Holdsworth

Adrian G. Wills

Thomas B. Schon

Brett Ninness

Format Sitasi

APA MLA BibTeX

Hendriks, J.N., Holdsworth, J.R.Z., Wills, A.G., Schon, T.B., Ninness, B. (2021). Data to Controller for Nonlinear Systems: An Approximate Solution. https://arxiv.org/abs/2103.08782

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓