Model Predictive Estimation

Model Predictive Estimation is a state estimation framework that belongs to the class of predictive filtering methods, distinguished by its use of a dynamic system model to iteratively predict future states and optimize estimation accuracy over a receding horizon based on observed measurements.

199

Publications

7.7K

Citations

714

Authors

399

Institutions

Publications per year

2017–2026

89

Authors

714

  1. SB
    Sanjay Basu

    Stanford University, United States

    2 publications · 268 citations

    2

    h-index

  2. SM
    Stephen M. LaConte

    Virginia Tech, United States

    2 publications · 51 citations

    2

    h-index

  3. AY
    Annika Yu Wang

    University of Houston, United States

    2 publications · 51 citations

    2

    h-index

  4. JB
    James B. Rawlings

    University of Wisconsin–Madison, United States

    2 publications · 102 citations

    2

    h-index

  5. TS
    Thomas Sandholm

    Hewlett-Packard (United States), United States

    2 publications · 41 citations

    2

    h-index

1–5 of 714

Venues

  1. PLoS ONE

    4 publications · 186 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 188 citations

    4

    h-index

  3. Computers & Chemical Engineering

    3 publications · 83 citations

    3

    h-index

  4. Journal of Applied Psychology

    3 publications · 140 citations

    3

    h-index

  5. Australian Journal of Management

    2 publications · 70 citations

    2

    h-index

1–5