Title :
Neuro emission controller for minimizing cyclic dispersion in spark ignition engines
Author :
He, Pingan ; Jagannathan, S.
Author_Institution :
Dept. of Electr. & Comput. Eng, Missouri Univ., Rolla, MO, USA
Abstract :
A novel neural network (NN) controller is developed to control spark ignition (SI) engines at extreme lean conditions. The purpose of neurocontroller is to reduce the cyclic dispersion at lean operation even when the engine dynamics are unknown. The stability analysis of the closed-loop control system is given and the boundedness of all signals is ensured. Results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller. The neuro controller can also be extended to minimize engine emissions with high EGR levels, where similar complex cyclic dynamics are observed. Further, the proposed approach can be applied to control nonlinear systems that have similar structure as that of the engine dynamics.
Keywords :
air pollution control; closed loop systems; combustion; control system synthesis; ignition; internal combustion engines; neurocontrollers; nonlinear control systems; stability; air pollution control; baskstepping approach; closed-loop control system; controller design; cyclic dispersion; cyclic dynamics; engine combustion; engine control systems; extreme lean conditions; feedback; fuel consumption; high EGR levels; neural network; neuro emission controller; nonlinear control systems; spark ignition engines; stability analysis; Control systems; Engines; Ignition; Neural networks; Neurocontrollers; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Sparks; Stability analysis;
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1223926