@article{1a7f1d44a6234d529950455ea6292ab1,
title = "Minimum variance constrained estimator",
abstract = "This paper is concerned with the problem of state estimation for discrete-time linear systems in the presence of additional (equality or inequality) constraints on the state (or estimate). By use of the minimum variance duality, the estimation problem is converted into an optimal control problem. Two algorithmic solutions are described: the full information estimator (FIE) and the moving horizon estimator (MHE). The main result is to show that the proposed estimator is stable in the sense of an observer. The proposed algorithm is distinct from the standard algorithm for constrained state estimation based upon the use of the minimum energy duality. The two are compared numerically on the benchmark batch reactor process model.",
keywords = "Constrained estimation, Kalman filter, MHE, Minimum variance duality",
author = "Mishra, {Prabhat K.} and Girish Chowdhary and Mehta, {Prashant G.}",
note = "Funding Information: This work was supported in part by Navy, USA N00014-19-1-2373 and National Science Foundation, USA 1739874 . The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Ali Zemouche under the direction of Editor Torsten S{\"o}derstr{\"o}m. Funding Information: Prabhat K. Mishra is a post-doctoral research associate at Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, USA. He was awarded the Ph.D. degree in 2019 from Indian Institute of Technology Bombay, India. His doctoral study was supported by Ministry of Human Resource and Development, India, and he received a Swiss Government Excellence Scholarship in 2017 to study at EPFL, Switzerland, for a year. His research interests include predictive, adaptive and learning based control. Funding Information: Girish Chowdhary is an associate professor and Donald Biggar Willet faculty fellow, and ACES Office of Research Faculty fellow at UIUC. He holds a joint appointment with Agricultural and Biological Engineering and Computer Science, and has affiliate appointments in Aerospace Engineering, Electrical and Computer Engineering. He is a full member of the Coordinated Science Laboratory. He is the director of the Field Robotics and Engineering Research Hub (FRESH), the associate director for the National AI institute (AIFARMS) and the Chief Scientist of the Illinois Autonomous Farm. He received his Ph.D. in Aerospace Engineering with a focus on robotics and autonomy from Georgia Institute of Technology (2010). He was a postdoc at the Laboratory for Information and Decision Systems (LIDS) of the Massachusetts Institute of Technology (2011–2013), and an assistant professor at Oklahoma State University{\textquoteright}s Mechanical and Aerospace Engineering department (2013–2016). He has a bachelor{\textquoteright}s degree in Aerospace Engineering with honors from the Royal Melbourne Institute of Technology in Melbourne Australia (2003). After his bachelors, he also worked with the German Aerospace Center{\textquoteright}s (DLR{\textquoteright}s) Institute of Flight Systems for around three years (2003–2006). His work on neural network based adaptive flight control has led to several key advances to flight control and his Dave Ward memorial award by the Aerospace Guidance and Controls Committee. He won the AFOSR Young Investigator Award in 2015, and several best paper awards. He is author of over 90 publications in autonomy and robotics and a PI on NSF, Air Force Office of Scientific Research (AFOSR), NASA, Advanced Research Projects Agency-Energy (ARPA-E), and Department of Energy (DOE) grants and Office of Naval Research (ONR) Multidisciplinary University Research Initiatives (MURI). Dr. Chowdhary is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA), and a senior member of IEEE. Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd",
year = "2022",
month = mar,
doi = "10.1016/j.automatica.2021.110106",
language = "English (US)",
volume = "137",
journal = "Automatica",
issn = "0005-1098",
publisher = "Elsevier Limited",
}