Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 18, Issue 8, Pages 951-961Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2005.03.008
Keywords
electronic throttle control; uncertainty; sliding mode; neural networks; adaptive control
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A neural network-based sliding mode controller for an electronic throttle of an internal combustion engine is proposed. Electronic throttle is modeled as a linear system with uncertainties and affected by disturbances depending on the states of the system. The disturbances, consisting of an unknown friction and a torque caused by the dual spring mechanism inside the mechanical part of the throttle, are estimated by a neural network whose parameters are adapted on-line. The sliding mode controller and the parameters adaptation scheme are derived in order to achieve a tracking of a smooth reference signal, while preserving boundedness of all signals in the closed-loop system. Experimental results are presented which demonstrate the efficiency and robustness of the proposed control scheme. (c) 2005 Elsevier Ltd. All rights reserved.
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