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Neural Computing and Applications

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01.12.2013 | Original Article

Genetic algorithm-based adaptive fuzzy sliding mode controller for electronic throttle valve

verfasst von: Xiaofang Yuan, Yimin Yang, Hui Wang, Yaonan Wang

Erschienen in: Neural Computing and Applications | Sonderheft 1/2013

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Abstract

Electronic throttle valves are electromechanical systems which regulate the air flow inside gasoline engines. The objective of electronic throttle valve control is to ensure fast and accurate reference tracking of the valve plate angle. This control demands are hard to accomplish since the plant is burdened with strong nonlinear effects and parameters uncertainty. In this paper, a genetic algorithm-based adaptive fuzzy sliding mode controller (AFSMC) is proposed for an electronic throttle considering actuator nonlinearities. In the AFSMC approach, fuzzy logic system is applied to approximate the plant model and the actuator model, the sliding mode controller makes full use of the plant model to guarantee robust control even in the presence of parameters uncertainty, and genetic algorithm is developed to search the optimal control gains values of the AFSMC. The performance of the AFSMC is verified by computer simulation and experiment.

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Titel: Genetic algorithm-based adaptive fuzzy sliding mode controller for electronic throttle valve
verfasst von: Xiaofang Yuan
Yimin Yang
Hui Wang
Yaonan Wang
Publikationsdatum: 01.12.2013
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe Sonderheft 1/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-1327-1

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