Title :
A Neuro-augmented Observer for a Class of Nonlinear Systems
Author :
Gong, Huajun ; Xu, Hao ; Chowdhury, Fahmida N.
Author_Institution :
Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
Abstract :
A new type of state observer for nonlinear systems is presented in this paper. This observer is a hybrid of linear and nonlinear parts: it is based on a conventional linear observer design, and augmented by a neural network. The neural network approximates only the nonlinear part of the system. The state estimation error is proved to approach zero asymptotically.
Keywords :
neurocontrollers; nonlinear control systems; observers; linear observer design; neural network; neuro-augmented observer; nonlinear systems; state observer; Convergence; Design methodology; Fault detection; NASA; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Observers; State estimation; State feedback;
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
DOI :
10.1109/IJCNN.2006.247100
