Abstract Machine learning (ML) and a nonlinear model predictive controller (NMPC) are
used in this paper to minimize the emissions and fuel consumption of a compression ignition …

In this work, we develop a model predictive control scheme for nonlinear systems using
autoencoder-based reduced-order machine learning models. First, an autoencoder is …

This paper proposes a nonlinear Economic Model Predictive Control (eMPC) strategy for the
airpath management of diesel engines with dual-loop Exhaust Gas Recirculation (EGR) and …

This paper deals with a control design problem for a diesel engine air path system that has
strong nonlinearity and requires multi-input and multi-output control to satisfy requirements …

This study presents an integrated control scheme of a diesel engine which aims to ensure
quick torque response while limiting the average NOx emission below the certain …

Abstract A supervisory Model Predictive Control (MPC) approach is developed for an air
path system for multi-mode operation in a diesel engine. MPC is a control method based on …

We propose a novel optimal estimation methodology for gasoline engine LP (low-pressure)
EGR (exhaust gas recirculation) air-path system, which allows us to implement virtual …

Emission regulations are becoming tighter, and Real Driving Emissions (RDE) is proposed
as a testing cycle for evaluating modern engine emissions under a wide operation range …

The control of the engine airpath is a constrained multi-objective tracking problem. Multiple
control variables including Exhaust Gas Recirculation (EGR) and Variable Nozzle …

This study proposes a model predictive control framework using a mixed integer
programming for the deep neural network (DNN) model with rectified linear unit (ReLU). The …