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Modeling, Simulation and Optimization of Complex Processes HPSC 2015 pp 165–177Cite as

An All-Interaction Matrix Approach to Linear and Bilinear System Identification

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Abstract

This paper is a brief introduction to the interaction matrices. Originally formulated as a parameter compression mechanism, the interaction matrices offer a unifying framework to treat a wide range of problems in system identification and control. We retrace the origin of the interaction matrices, and describe their applications in selected problems in system identification.

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Author information

Authors and Affiliations

  1. Thayer School of Engineering, Dartmouth College, Hanover, NH, 03755, USA

    Minh Q. Phan

  2. Philips Research, New York, NY, USA

    Francesco Vicario

  3. Department of Mechanical Engineering, Columbia University, New York, NY, USA

    Richard W. Longman

  4. Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY, USA

    Raimondo Betti

Authors
  1. Minh Q. Phan
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  2. Francesco Vicario
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  3. Richard W. Longman
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  4. Raimondo Betti
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Corresponding author

Correspondence to Minh Q. Phan .

Editor information

Editors and Affiliations

  1. Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany

    Hans Georg Bock

  2. Institute of Mathematics, Vietnam Academy of Science and Technology, Hanoi, Vietnam

    Hoang Xuan Phu

  3. Institute of Applied Mathematics, Heidelberg University, Heidelberg, Germany

    Rolf Rannacher

  4. Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany

    Johannes P. Schlöder

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Phan, M.Q., Vicario, F., Longman, R.W., Betti, R. (2017). An All-Interaction Matrix Approach to Linear and Bilinear System Identification. In: Bock, H., Phu, H., Rannacher, R., Schlöder, J. (eds) Modeling, Simulation and Optimization of Complex Processes HPSC 2015 . Springer, Cham. https://doi.org/10.1007/978-3-319-67168-0_14

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