Title :
The development of Model Predictive Control in automotive industry: A survey
Author :
Hrovat, Davor ; Di Cairano, Stefano ; Tseng, H. Eric ; Kolmanovsky, Ilya V.
Author_Institution :
Ford Res. & Adv. Eng., Dearborn, MI, USA
Abstract :
Model Predictive Control (MPC) is an established control technique in chemical process control, due to its capability of optimally controlling multivariable systems with constraints on plant and actuators. In recent years, the advances in MPC algorithms and design processes, the increased computational power of electronic control units, and the need for improved performance, safety and reduced emissions, have drawn considerable interest in MPC from the automotive industry. In this paper we survey the investigations of MPC in the automotive industry with particular focus on the developments at Ford Motor Company. First, we describe the basic MPC techniques used in the automotive industry, and the early exploratory investigations. Then we present three applications that have been recently prototyped in fully functional production-like vehicles, highlighting the features that make MPC a good candidate strategy for each case. We finally present our perspectives on the next challenges and future applications of MPC in the automotive industry.
Keywords :
automobile industry; multivariable control systems; predictive control; Ford Motor Company; MPC; automotive industry; chemical process control; electronic control unit; model predictive control; multivariable system; Actuators; Automotive engineering; Engines; Magnetic materials; Photonic crystals; Sparks; Vehicles;
Conference_Titel :
Control Applications (CCA), 2012 IEEE International Conference on
Conference_Location :
Dubrovnik
Print_ISBN :
978-1-4673-4503-3
Electronic_ISBN :
1085-1992
DOI :
10.1109/CCA.2012.6402735