DocumentCode
114927
Title
Multi-parametric extremum seeking-based auto-tuning for robust Input-Output linearization control
Author
Benosman, Mouhacine
Author_Institution
Mitsubishi Electr. Res. Labs., Cambridge, MA, USA
fYear
2014
fDate
15-17 Dec. 2014
Firstpage
2685
Lastpage
2690
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.
Keywords
feedback; iterative methods; learning systems; linearisation techniques; mechatronics; nonlinear control systems; optimal control; robust control; MES control; additive uncertainties; global uniform boundedness; input-output linearizable nonlinear systems; iterative autotuning; iterative feedback gain tuning problem; mechatronics; model-free learning algorithm; model-free multiparametric extremum seeking control; nominal input-output linearization-based controller design; numerical tests; output tracking error dynamics; robust nonlinear controller; stability analysis; Coils; Cost function; Robustness; Trajectory; Tuning; Uncertainty; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
978-1-4799-7746-8
Type
conf
DOI
10.1109/CDC.2014.7039800
Filename
7039800
Link To Document