12 citations · 22 across the 7 of their papers we have counts for
8 papers · 1 filter
Model Predictive Control of Diesel Engine Emissions Based on Neural Network Modeling
Jiadi Zhang, Xiao Li, Ilya Kolmanovsky +2
This paper addresses the control of diesel engine nitrogen oxides (NOx) and Soot emissions through the application of Model Predictive Control (MPC). The developments described in…
Modeling and Control of Diesel Engine Emissions using Multi-layer Neural Networks and Economic Model Predictive Control
Jiadi Zhang, Xiao Li, Mohammad Reza Amini +3
This paper presents the results of developing a multi-layer Neural Network (NN) to represent diesel engine emissions and integrating this NN into control design. Firstly, a NN is t…
Benefits of Feedforward for Model Predictive Airpath Control of Diesel Engines
Jiadi Zhang, Mohammad Reza Amini, Ilya Kolmanovsky +2
This paper investigates options to complement a diesel engine airpath feedback controller with a feedforward. The control objective is to track the intake manifold pressure and exh…
Development of a Model Predictive Airpath Controller for a Diesel Engine on a High-Fidelity Engine Model with Transient Thermal Dynamics
Jiadi Zhang, Mohammad Reza Amini, Ilya Kolmanovsky +2
This paper presents the results of a model predictive controller (MPC) development for diesel engine air-path regulation. The control objective is to track the intake manifold pres…
Active Learning for Linear Parameter-Varying System Identification
Robert Chin, Alejandro I. Maass, Nalika Ulapane +5
Active learning is proposed for selection of the next operating points in the design of experiments, for identifying linear parameter-varying systems. We extend existing approaches…
Tuning of multivariable model predictive controllersthrough expert bandit feedback
Alex. S. Ira, Chris Manzie, Iman Shames +4
For certain industrial control applications an explicit function capturing the nontrivial trade-off between competing objectives in closed loop performance is not available. In suc…