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**Harvard**

Kianfar, R. och Wik, T. (2010) *Automated Controller Design using Linear Quantitative Feedback Theory for Nonlinear systems*.

** BibTeX **

@conference{

Kianfar2010,

author={Kianfar, Roozbeh and Wik, Torsten},

title={Automated Controller Design using Linear Quantitative Feedback Theory for Nonlinear systems},

booktitle={Reglermöte 2010},

abstract={A method to design simple linear controllers for mildly nonlinear systems is presented. In order to design the
desired controller we approximate the behavior of the nonlinear system with a set of linear systems which are derived through linearizations. Classical local linearization is carried out around stationary points but in order to have a better approximation of the nonlinear system selected non-stationary points are taken into account as well. This set of linear models are considered as an uncertainty description for a nominal plant. Quantitative Feedback theory (QFT) may be used to guarantee specification to be fulfilled for all linear models in such an uncertainty set. Traditionally QFT design is carried out in a Nichols diagram by loop shaping of the nominal linear plant. This task highly depends on the experience of the designer and is difficult for unstable systems. In order to facilitate this task an optimization algorithm based on Genetic algorithm is used to automatically synthesize a fixed structure controller. For illustration and evaluation the method is succesfully applied to a Wiener system and a nonlinear Bioreactor benchmark problem.},

year={2010},

keywords={Nonlinear, QFT, loop shaping, linearization, non-stationary point, genetic algorithm},

}

** RefWorks **

RT Conference Proceedings

SR Print

ID 134382

A1 Kianfar, Roozbeh

A1 Wik, Torsten

T1 Automated Controller Design using Linear Quantitative Feedback Theory for Nonlinear systems

YR 2010

T2 Reglermöte 2010

AB A method to design simple linear controllers for mildly nonlinear systems is presented. In order to design the
desired controller we approximate the behavior of the nonlinear system with a set of linear systems which are derived through linearizations. Classical local linearization is carried out around stationary points but in order to have a better approximation of the nonlinear system selected non-stationary points are taken into account as well. This set of linear models are considered as an uncertainty description for a nominal plant. Quantitative Feedback theory (QFT) may be used to guarantee specification to be fulfilled for all linear models in such an uncertainty set. Traditionally QFT design is carried out in a Nichols diagram by loop shaping of the nominal linear plant. This task highly depends on the experience of the designer and is difficult for unstable systems. In order to facilitate this task an optimization algorithm based on Genetic algorithm is used to automatically synthesize a fixed structure controller. For illustration and evaluation the method is succesfully applied to a Wiener system and a nonlinear Bioreactor benchmark problem.

LA eng

OL 30