Name
Title | ||
|---|---|---|
MIMO Neural Models for a Twin-Rotor Platform - Comparison Between Mathematical Simulations and Real Experiments. |
Abstract | ||
|---|---|---|
This work presents a neural model developed for a multivariable system with complex nonlinear dynamics, obtained through a tight methodology used both in simulation and in the real platform. In addition, this neural model has been studied and designed to meet the requirements of a predictive control strategy. A Twin-Rotor platform is used as an example of a Multi-Input Multi-Output (MIMO) system to study and analyse how a neural network is able to reproduce its nonlinear coupled dynamics and accurately estimate future system outputs. An in-depth study of the neural structures and their performance in the prediction of future states has been developed. Results show with comparisons, the modelization inaccuracies that appears when a proposal made just on the basis of a mathematical simulation is used to conclude the good performance of these MIMO neural models. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-3-030-57802-2_39 | SOCO |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kerman Viana | 1 | 0 | 0.34 |
| Mikel Larrea | 2 | 267 | 30.10 |
| Eloy Irigoyen | 3 | 38 | 14.23 |
| Mikel Diez | 4 | 0 | 0.34 |
| Asier Zubizarreta | 5 | 37 | 12.30 |