TY - JOUR
T1 - Combustion Control of Diesel Engine using Feedback Error Learning with Kernel Online Learning Approach
AU - Widayaka, Elfady Satya
AU - Ohmori, Hiromitsu
N1 - Funding Information:
This research is done as part of Control and System Modelling on Fuel Technology Innovation (Research Leader: Shigehiko Kaneko of Tokyo University) of SIP (Strategic Innovation Program) under Japan Science and Technology Agency (JST).
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2016/10/3
Y1 - 2016/10/3
N2 - This paper shows how to design Multivariable Model Reference Adaptive Control System (MRACS) for "Tokyo University discrete-time engine model" proposed by Yasuda et al (2014). This controller configuration has the structure of "Feedback error learning (FEL)" and adaptive law is based on kernel method. Simulation results indicate that "kernelized" adaptive controllers can improve the tracking performance, the speed of convergence and the robustness to disturbances.
AB - This paper shows how to design Multivariable Model Reference Adaptive Control System (MRACS) for "Tokyo University discrete-time engine model" proposed by Yasuda et al (2014). This controller configuration has the structure of "Feedback error learning (FEL)" and adaptive law is based on kernel method. Simulation results indicate that "kernelized" adaptive controllers can improve the tracking performance, the speed of convergence and the robustness to disturbances.
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U2 - 10.1088/1742-6596/744/1/012107
DO - 10.1088/1742-6596/744/1/012107
M3 - Conference article
AN - SCOPUS:84994112039
SN - 1742-6588
VL - 744
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012107
T2 - 13th International Conference on Motion and Vibration Control, MOVIC 2016 and the 12th International Conference on Recent Advances in Structural Dynamics, RASD 2016
Y2 - 4 July 2016 through 6 July 2016
ER -