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, December 2014, pp. 2685-2690.
      BibTeX TR2014-108 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 = {https://www.merl.com/publications/TR2014-108}
      • }
  • Research Areas:

    Control, Optimization, Dynamical Systems

Abstract:

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.