TY - JOUR
T1 - Feedback error learning control using OS-ELM for SI engine airpath systems
AU - Wang, Dongyang
AU - Hashimoto, Yuhki
AU - Ohmori, Hiromitsu
N1 - Publisher Copyright:
© 2021 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
PY - 2021
Y1 - 2021
N2 - Currently, due to the stricter emission legislation, spark-ignition (SI) engine with low pressure exhaust gas recirculation (LP-EGR) has become a research hotspot. However, with the increasing complexity of engine, it is difficult to obtain sufficient control performance by conventional MAP control or PID control. This paper focuses on the airpath system of a SI engine with low pressure EGR, proposes a new model-based control method for the model of the airpath system based on the Feedback Error Learning control using online sequential-extreme learning machine (OS-ELM) as controller algorithm. In this paper, the airpath model has been built and effectiveness of the proposed control method has been confirmed on the model.
AB - Currently, due to the stricter emission legislation, spark-ignition (SI) engine with low pressure exhaust gas recirculation (LP-EGR) has become a research hotspot. However, with the increasing complexity of engine, it is difficult to obtain sufficient control performance by conventional MAP control or PID control. This paper focuses on the airpath system of a SI engine with low pressure EGR, proposes a new model-based control method for the model of the airpath system based on the Feedback Error Learning control using online sequential-extreme learning machine (OS-ELM) as controller algorithm. In this paper, the airpath model has been built and effectiveness of the proposed control method has been confirmed on the model.
KW - Adaptive learning control
KW - Air path system
KW - EGR
KW - Feedback error learning
KW - OS-ELM
KW - SI engine
UR - http://www.scopus.com/inward/record.url?scp=85120726589&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85120726589&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2021.10.161
DO - 10.1016/j.ifacol.2021.10.161
M3 - Conference article
AN - SCOPUS:85120726589
SN - 2405-8963
VL - 54
SP - 182
EP - 188
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
IS - 10
T2 - 6th IFAC Conference on Engine Powertrain Control, Simulation and Modeling E-COSM 2021
Y2 - 23 August 2021 through 25 August 2021
ER -