Abstract
Design principle of exhaust gas recirculation (EGR) control for modern diesel engine is based on MAP which is available to experiment. The MAP is a need to a number of experiments with engine load characteristic curve, which is a heavy work. The MAP available cannot be used for all the range exactly in the experiments including changes of engine running conditions. Therefore, it is very difficult to design a PID controller based on MAP to adjust the controller with a bad robustness. Directing against the existing situation, a controller on the basis of an artificial neural network (ANN), which is of rapid adjustment and good robustness, is proposed in this chapter. It is experimentally proved to apply the control system that implements exhaust emission effectively controlled and reduced.
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© 2013 Springer-Verlag London
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Ruan, G.Q., Zhang, Z.D., Wang, Q. (2013). EGR Control System Based on ANN. In: Zhong, Z. (eds) Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012. Lecture Notes in Electrical Engineering, vol 218. Springer, London. https://doi.org/10.1007/978-1-4471-4847-0_12
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DOI: https://doi.org/10.1007/978-1-4471-4847-0_12
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