Multiple-Input Multiple-Output Model Predictive Control of a Diesel Engine

Traditionally, diesel engine control has had to rely on indirect feedback variables and empirical open-loop maps because direct measurements of the variables representing high-level objectives, such as emissions, have not been available in production engines. With new sensors being developed, the opportunity opens to design the controller directly based on high-level objectives. In this paper, we propose to use model predictive control as a systematic way to go directly from high-level specifications to a control algorithm. The controller uses four actuator variables and five measured variables and is based on a model obtained through system identification. Experimental results on a six-cylinder heavy-duty engine around a fixed operating point demonstrate the potential of the control scheme.