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Combustion Control of Diesel Engine using Feedback Error Learning with Kernel Online Learning Approach

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Published under licence by IOP Publishing Ltd
, , Citation Elfady Satya Widayaka and Hiromitsu Ohmori 2016 J. Phys.: Conf. Ser. 744 012107 DOI 10.1088/1742-6596/744/1/012107

1742-6596/744/1/012107

Abstract

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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