Volume 2 Number 2
December 2005
Article Contents
Shi-Wei Wang and Ding-Li Yu. Adaptive Air-Fuel Ratio Control with MLP Network. International Journal of Automation and Computing, vol. 2, no. 2, pp. 125-133, 2005. doi: 10.1007/s11633-005-0125-y
Cite as: Shi-Wei Wang and Ding-Li Yu. Adaptive Air-Fuel Ratio Control with MLP Network. International Journal of Automation and Computing, vol. 2, no. 2, pp. 125-133, 2005. doi: 10.1007/s11633-005-0125-y

Adaptive Air-Fuel Ratio Control with MLP Network

  • Received: 2005-06-28
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Adaptive Air-Fuel Ratio Control with MLP Network

Abstract: This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller. A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC.

Shi-Wei Wang and Ding-Li Yu. Adaptive Air-Fuel Ratio Control with MLP Network. International Journal of Automation and Computing, vol. 2, no. 2, pp. 125-133, 2005. doi: 10.1007/s11633-005-0125-y
Citation: Shi-Wei Wang and Ding-Li Yu. Adaptive Air-Fuel Ratio Control with MLP Network. International Journal of Automation and Computing, vol. 2, no. 2, pp. 125-133, 2005. doi: 10.1007/s11633-005-0125-y
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