Abstract
KEYWORDS Model-Based, Control, Multivariable, Air Charge, Feedback Linearization
ABSTRACT
During the last years, diesel engines are becoming increasingly complex, coupling several hardware components in order to increase fuel economy and to reduce emissions. A big effort from a control and calibration point of view is required in order to optimize the coordination among them. Furthermore, the air-path process is highly nonlinear, based on thermodynamic phenomena. The objective of this study is to investigate a nonlinear model-based multivariable (MIMO, Multi Input Multi Output) technique to decouple actuators interaction and to reduce the calibration effort, while increasing control performances and robustness with respect to model uncertainties and system parameter variations.
The presented methodology uses a nonlinear physical model of the diesel air and charging system, and the control architecture is mainly based on the feedback linearization technique that decouples actuators’ interactions and compensates for nonlinearities. System differential equations are transformed through the Feedback Linearization in order to define a new set of virtual inputs. Relation among the new virtual inputs and the outputs is purely linear and decoupled, meaning that each virtual input affects linearly only one output. Moreover, a linear control block is added to guarantee requested transient and steady state performances and closed loop robustness. This additional control block is composed by four SISO (Single Input Single Output) linear controllers (e.g. four PID controls) tuned over the obtained linear system.