Title :
Convex optimization in identification of stable non-linear state space models
Author :
Tobenkin, Mark M. ; Manchester, Ian R. ; Wang, Jennifer ; Megretski, Alexandre ; Tedrake, Russ
Author_Institution :
Comput. Sci. & Artificial Intell. Lab., Massachusetts Inst. of Technol., Cambridge, MA, USA
Abstract :
A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined as a measure of robustness of the simulation error with respect to equation errors. Basic definitions and analytical results are presented. The utility of the method is illustrated on a simple simulation example as well as experimental recordings from a live neuron.
Keywords :
convex programming; nonlinear systems; state-space methods; convex optimization; equation error; nonlinear state space equation; nonlinear system identification; robustness measure; simulation error; stable nonlinear state space model identification; Data models; Equations; Linear systems; Mathematical model; Robustness; Stability analysis; Upper bound;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5718114
