Linear Model Predictive Control

Linear Model Predictive Control is a model predictive control strategy that uses a linear dynamic model of the system to predict future behavior and compute optimal control inputs by solving a quadratic optimization problem over a finite horizon, distinguishing it from nonlinear or hybrid variants through its reliance on linear system assumptions and convex formulation.

841

Publications

63.5K

Citations

1.9K

Authors

643

Institutions

Publications per year

2017–2026

309

Variants

Linear Mpc

Authors

1.9K

  1. AB
    Alberto Bemporad

    University of Siena, Italy

    31 publications · 3.3K citations

    24

    h-index

  2. MM
    Manfred Morari

    ETH Zurich, Switzerland

    21 publications · 11.6K citations

    19

    h-index

  3. FA
    Frank Allgöwer

    University of Stuttgart, Germany

    17 publications · 1.5K citations

    14

    h-index

  4. JB
    James B. Rawlings

    University of Wisconsin–Madison, United States

    11 publications · 1.7K citations

    11

    h-index

  5. FB
    Francesco Borrelli

    University of California, Berkeley, United States

    12 publications · 2K citations

    11

    h-index

1–5 of 1.9K

Venues

  1. Automatica

    39 publications · 13.8K citations

    31

    h-index

  2. IEEE Transactions on Automatic Control

    37 publications · 4.7K citations

    28

    h-index

  3. Journal of Process Control

    21 publications · 1.4K citations

    17

    h-index

  4. IFAC Proceedings Volumes

    29 publications · 1.1K citations

    17

    h-index

  5. IEEE Transactions on Control Systems Technology

    16 publications · 1.3K citations

    16

    h-index

1–5