Automated Controller Design using Linear Quantitative Feedback Theory for Nonlinear systems
Paper in proceeding, 2009

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. Qunatitative 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.

non-stationary point

loop shaping

QFT

linearization

genetic algorithm.

Nonlinear

Author

Roozbeh Kianfar

Chalmers, Signals and Systems, Systems and control

Torsten Wik

Chalmers, Signals and Systems, Systems and control

Proc. 7th IEEE International Conference on Control and Automation, Dec. 9-11, Christchurch, New Zealand

Vol. 1-3 1955-1961
978-1-4244-4706-0 (ISBN)

Subject Categories

Industrial Biotechnology

Chemical Engineering

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/ICCA.2009.5410365

ISBN

978-1-4244-4706-0

More information

Created

10/8/2017