TR2014-090

Extremum Seeking-based Adaptive Control for Electromagnetic Actuators


    •  Benosman, M.; Atinc, G.M., "Extremum Seeking-based Adaptive Control for Electromagnetic Actuators", International Journal of Control, DOI: 10.1080/00207179.2014.964779, September 2014.
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      • @article{Benosman2014sep2,
      • author = {Benosman, M. and Atinc, G.M.},
      • title = {Extremum Seeking-based Adaptive Control for Electromagnetic Actuators},
      • journal = {International Journal of Control},
      • year = 2014,
      • month = sep,
      • publisher = {Taylor & Francis Group},
      • doi = {10.1080/00207179.2014.964779},
      • url = {http://www.merl.com/publications/TR2014-090}
      • }
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  • Research Areas:

    Control, Dynamical Systems


In this paper we present a learning-based adaptive method to solve the problem of robust trajectory tracking for electromagnetic actuators. We merge a nonlinear backstepping controller that ensures bounded input/bounded states stability, with a multi-variable extremum seeking (MES) model-free learning algorithm. The learning algorithm is used to estimate online the uncertain parameters of the model, in this sense we propose a learning-based adaptive controller. We present a proof of stability of this learning-based nonlinear controller when considering uncertainties with linear parametrization. The efficiency of this approach is shown on a numerical example.