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.

Meeting Name

International Joint Conference on Neural Networks, 2003


Electrical and Computer Engineering

Second Department

Computer Science


National Science Foundation (U.S.)

Keywords and Phrases

Closed Loop Systems; Control System Synthesis; Neurocontrollers; Air pollution; Combustion; Internal combustion engines; Nonlinear control theory; Spark ignition engines -- Ignition; Stability

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2003 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 2003