TR2016-059

Multi-Parametric Extremum Seeking-based Iterative Feedback Gains Tuning for Nonlinear Control


    •  Benosman, M., "Multi-Parametric Extremum Seeking-based Iterative Feedback Gains Tuning for Nonlinear Control", International Journal of Robust and Nonlinear Control, DOI: 10.1002/rnc.3547, Vol. 26, No. 18, pp. 4035-4055, May 2016.
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      • @article{Benosman2016may,
      • author = {Benosman, M.},
      • title = {Multi-Parametric Extremum Seeking-based Iterative Feedback Gains Tuning for Nonlinear Control},
      • journal = {International Journal of Robust and Nonlinear Control},
      • year = 2016,
      • volume = 26,
      • number = 18,
      • pages = {4035--4055},
      • month = may,
      • doi = {10.1002/rnc.3547},
      • url = {http://www.merl.com/publications/TR2016-059}
      • }
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    Mechatronics


We study in this paper the problem of iterative feedback gains auto-tuning for a class of nonlinear systems. For the class of Input-Output linearizable nonlinear systems with bounded additive uncertainties, we first design a nominal Input-Output linearization-based robust controller that ensures global uniform boundedness of the output tracking error dynamics. Then, we complement the robust controller with a model-free multi-parametric extremum seeking (MES) control to iteratively auto-tune
the feedback gains. We analyze the stability of the whole controller, i.e., robust nonlinear controller combined with the MES model-free learning algorithm. We use numerical tests to demonstrate the performance of this method on a mechatronics example.