Publicación:
Self-tuning NMPC of an engine air path
Self-tuning NMPC of an engine air path
| dc.contributor.author | Mendoza D. | es_PE |
| dc.contributor.author | Schrangl P. | es_PE |
| dc.contributor.author | Ipanaqué W. | es_PE |
| dc.contributor.author | del Re L. | es_PE |
| dc.date.accessioned | 2024-05-30T23:13:38Z | |
| dc.date.available | 2024-05-30T23:13:38Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Many automotive systems such as engines have manufacturing tolerances or change over time. This limits the performance of controllers tuned for the nominal case. A robust controller can not always overcome this performance gap. Against this background, in this work, we propose a self-tuning control strategy for an engine air path model obtained from data of a real engine and show its benefits setting. The self-tuning control consists of an online parameter estimation algorithm for polynomial non-linear autoregressive with exogenous input (PNARX) models and a nonlinear model predictive controller (NMPC) implemented by the continuation/generalized minimum residual (C/GMRES) algorithm. In a first step design of experiments (DOE) is utilized to identify a PNARX model offline from measurements performed on an engine test bed. A tracking NMPC is designed for this model and applied in simulation on the identified model. The control performance is assessed for the case of a wrong initial guess. It is shown that the resulting performance gap can be overcome by the online parameter estimation of a k-step prediction model with directional forgetting. An improved closed loop control performance of the air path model confirms the approach. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license | |
| dc.description.sponsorship | Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec | |
| dc.identifier.doi | https://doi.org/10.1016/j.ifacol.2020.12.899 | |
| dc.identifier.scopus | 2-s2.0-85105043963 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12390/2619 | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier B.V. | |
| dc.relation.ispartof | IFAC-PapersOnLine | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | System identification | |
| dc.subject | Adaptive control | es_PE |
| dc.subject | Automotive control | es_PE |
| dc.subject | Predictive control | es_PE |
| dc.subject.ocde | http://purl.org/pe-repo/ocde/ford#1.05.09 | |
| dc.title | Self-tuning NMPC of an engine air path | |
| dc.type | info:eu-repo/semantics/article | |
| dspace.entity.type | Publication |