Tuning nonlinear state-space models using unconstrained multiple shooting
| Autor: | Mark Runacres, Joannes Schoukens, Jan Rik Decuyper, Koen Tiels |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Van der Pol oscillator Mathematical optimization Computer science 020208 electrical & electronic engineering Stability (learning theory) 02 engineering and technology Nonlinear optimisation Parameter space Nonlinear state-space models Parameter identification problem Nonlinear system 020901 industrial engineering & automation Unconstrained multiple shooting Control and Systems Engineering Bounded function 0202 electrical engineering electronic engineering information engineering Benchmark (computing) State space Unstable initialisation |
| Zdroj: | IFAC-PapersOnLine. 53:334-340 |
| ISSN: | 2405-8963 |
| DOI: | 10.1016/j.ifacol.2020.12.182 |
| Popis: | A persisting challenge in nonlinear dynamical modelling is parameter inference from data. Provided that an appropriate model structure was selected, the identification problem is profoundly affected by a choice of initialisation. A particular challenge that may arise is initialisation within a region of the parameter space where the model is not contractive. Exploring such regions is not feasible using the conventional optimisation tools for they require a bounded evaluation of the cost. This work proposes an unconstrained multiple shooting technique, able to mitigate stability issues during the optimisation of nonlinear state-space models. The technique is illustrated on simulation results of a Van der Pol oscillator and benchmark results on a Bouc-Wen hysteretic system. |
| Databáze: | OpenAIRE |
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