Feedback Error Learning Control for Airpath System by Using Oxygen Concentration Adaptive Observer

Abstract

To deal with stringent exhaust emission regulations, an exhaust gas recirculation (EGR) system is widely used in internal combustion engines. However, appropriate control of EGR is difficult because of the gas transport delay and unavailability of the EGR rate. In this paper, a model-based control approach for engine airpath systems is proposed. A physical model of engine airpath considering the transport delay in EGR is constructed. An adaptive observer is introduced to estimate the EGR rate by using available quantities. Feedback error learning control is applied to the airpath system to deal with a characteristic change of the controlled plant. We validate the proposed method by numerical simulations.