TR2014-108

Multi-Parametric Extremum Seeking-Based Auto-Tuning for Robust Input-Output Linearization Control


    •  Benosman, M., "Multi-Parametric Extremum Seeking-Based Auto-Tuning for Robust Input-Output Linearization Control", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC.2014.7039800, ISBN: 978-1-4799-7746-8, December 2014, pp. 2685-2690.
      BibTeX Download PDF
      • @inproceedings{Benosman2014dec,
      • author = {Benosman, M.},
      • title = {Multi-Parametric Extremum Seeking-Based Auto-Tuning for Robust Input-Output Linearization Control},
      • booktitle = {IEEE Conference on Decision and Control (CDC)},
      • year = 2014,
      • pages = {2685--2690},
      • month = dec,
      • publisher = {IEEE},
      • doi = {10.1109/CDC.2014.7039800},
      • isbn = {978-1-4799-7746-8},
      • url = {http://www.merl.com/publications/TR2014-108}
      • }
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  • Research Areas:

    Control, Optimization, Dynamical Systems


We study in this paper the problem of iterative feedback gains tuning for a class of nonlinear systems. We consider Input-Output linearizable nonlinear systems with additive uncertainties. We first design a nominal Input-Output linearization-based 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 plus model-free learning algorithm. We use numerical tests to demonstrate the performance of this method on a mechatronics example.