Citation
Ehsan Elhamifar, Sam Burden, Shankar Sastry. "Adaptive Piecewise-Affine Inverse Modeling of Hybrid Dynamical Systems". World Congress of the International Federation of Automatic Control (IFAC), 2014.

Abstract
Motivated by the study of complex motor control systems, we consider the identification and control of PieceWise Affine (PWA) systems and propose a novel data-driven framework that adaptively inverts the dynamics of such systems using noisy sampled data. First, we propose a novel PWA identification algorithm based on convex optimization applicable to both state{space and input/output models. Given a PWA model of the dynamics obtained from the identification algorithm, we consider the control of the resulting hybrid system where our goal is to find an input that reproduces a given reference trajectory or that extremizes a performance criterion. We demonstrate our proposed framework on a model of a jumping robot.

Electronic downloads

• HSID-IFAC14-Ehsan.pdf · application/pdf · 767 kbytes

• HTML

  Ehsan Elhamifar, Sam Burden, Shankar Sastry. <a
  href="http://robotics.eecs.berkeley.edu/pubs/5.html"
  >Adaptive Piecewise-Affine Inverse Modeling of Hybrid
  Dynamical Systems</a>, World Congress of the
  International Federation of Automatic Control (IFAC), 2014.

• Plain text

  Ehsan Elhamifar, Sam Burden, Shankar Sastry. "Adaptive
  Piecewise-Affine Inverse Modeling of Hybrid Dynamical
  Systems". World Congress of the International
  Federation of Automatic Control (IFAC), 2014.

• BibTeX

  @inproceedings{ElhamifarBurdenSastry14_AdaptivePiecewiseAffineInverseModelingOfHybridDynamical,
      author = {Ehsan Elhamifar and Sam Burden and Shankar Sastry},
      title = {Adaptive Piecewise-Affine Inverse Modeling of
                Hybrid Dynamical Systems},
      booktitle = {World Congress of the International Federation of
                Automatic Control (IFAC)},
      year = {2014},
      abstract = {Motivated by the study of complex motor control
                systems, we consider the identification and
                control of PieceWise Affine (PWA) systems and
                propose a novel data-driven framework that
                adaptively inverts the dynamics of such systems
                using noisy sampled data. First, we propose a
                novel PWA identification algorithm based on convex
                optimization applicable to both state{space and
                input/output models. Given a PWA model of the
                dynamics obtained from the identification
                algorithm, we consider the control of the
                resulting hybrid system where our goal is to find
                an input that reproduces a given reference
                trajectory or that extremizes a performance
                criterion. We demonstrate our proposed framework
                on a model of a jumping robot.},
      URL = {http://robotics.eecs.berkeley.edu/pubs/5.html}
  }
  

Posted by Ehsan Elhamifar on 16 May 2014.
Groups: ehumans
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