Real-time optimization and model predictive control for aerospace and automotive applications

    •  Di Cairano, S., Kolmanovsky, I.V., "Real-time optimization and model predictive control for aerospace and automotive applications", American Control Conference (ACC), DOI: 10.23919/​ACC.2018.8431819, June 2018, pp. 2392-2409.
      BibTeX TR2018-086 PDF
      • @inproceedings{DiCairano2018jun,
      • author = {Di Cairano, Stefano and Kolmanovsky, Ilya V.},
      • title = {Real-time optimization and model predictive control for aerospace and automotive applications},
      • booktitle = {American Control Conference (ACC)},
      • year = 2018,
      • pages = {2392--2409},
      • month = jun,
      • doi = {10.23919/ACC.2018.8431819},
      • url = {}
      • }
  • MERL Contact:
  • Research Area:



In recent years control methods based on realtime optimization (RTO) such as model predictive control (MPC) have been investigated for a significant number of applications in the automotive and aerospace (A&A) domains. This paper provides a tutorial overview of RTO in automotive and aerospace, with particular focus on MPC which is probably the most largely investigated method. First, we review the features that make RTO appealing for A&A applications. Then, due to the model-based nature of these control methods, we describe the key first principle models and opportunities that these provide for RTO. Next, we detail the key steps and guidelines of the MPC design process which are tailored to A&A systems. Finally, we discuss numerical algorithms for implementing RTO, and their suitability for implementation in embedded computing platforms to in A&A domains


  • Related News & Events

    •  NEWS   MERL researcher Stefano Di Cairano taught short course for European Embedded Control Institute
      Date: June 10, 2019 - June 14, 2019
      Where: Paris
      MERL Contact: Stefano Di Cairano
      Research Areas: Control, Dynamical Systems, Optimization
      • MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
    •  NEWS   Control and Dynamical Systems members to deliver 10 papers at American Control Conference
      Date: June 26, 2018 - June 29, 2018
      Where: ACC2018 Milwakee
      MERL Contacts: Ankush Chakrabarty; Stefano Di Cairano; Uroš Kalabić; Rien Quirynen; Yebin Wang; Avishai Weiss
      Research Area: Control
      • At the American Control Conference June 26-29,, MERL members will give 10 papers on subjects including model predictive control, embedded optimization, urban path planning, motor control, estimation, and calibration.