Title :
Convex optimization in robust identification of nonlinear feedback
Author :
Megretski, Alexandre
Author_Institution :
EECS, MIT, MA, USA
Abstract :
A nonlinear system identification setup is formulated as a task of finding a stable feedback system of fixed complexity providing the best robust fit for a given set of input-output data. New techniques, based on incremental passivity, are proposed for casting such problems in a format which allows application of efficient convex optimization engines. Case studies of specific implementations of the approach are provided.
Keywords :
convex programming; feedback; identification; nonlinear systems; convex optimization; incremental passivity; nonlinear feedback; nonlinear system identification; robust identification; Casting; Control systems; Equations; Feedback; Nonlinear control systems; Nonlinear systems; Robust control; Robustness; System identification; Virtual manufacturing;
Conference_Titel :
Decision and Control, 2008. CDC 2008. 47th IEEE Conference on
Conference_Location :
Cancun
Print_ISBN :
978-1-4244-3123-6
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2008.4739470
