Title :
Dynamic neural network-based robust observers for second-order uncertain nonlinear systems
Author :
Dinh, H. ; Kamalapurkar, R. ; Bhasin, S. ; Dixon, W.E.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
A dynamic neural network (DNN) based robust observer for second-order uncertain nonlinear systems is developed. The observer structure consists of a DNN to estimate the system dynamics on-line, a dynamic filter to estimate the unmeasurable state and a sliding mode feedback term to account for modeling errors and exogenous disturbances. The observed states are proven to asymptotically converge to the system states though Lyapunov-based stability analysis.
Keywords :
Lyapunov methods; asymptotic stability; feedback; filtering theory; neurocontrollers; nonlinear control systems; observers; robust control; uncertain systems; variable structure systems; Lyapunov-based stability analysis; asymptotic converge; dynamic filter; dynamic neural network-based robust observers; exogenous disturbances; modeling errors; second-order uncertain nonlinear systems; sliding mode feedback term; system dynamic estimation; system states; unmeasurable state estimation; Artificial neural networks; Estimation error; Nonlinear dynamical systems; Observers; Robustness; Stability analysis;
Conference_Titel :
Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-61284-800-6
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2011.6160981
