DocumentCode :
2462349
Title :
Trajectory tracking based on differential neural networks for a class of nonlinear systems
Author :
Pérez-Cruz, J. Humberto ; Poznyak, Alexander
Author_Institution :
Dept. of Autom. Control, CINVESTAV-IPN, Mexico City, Mexico
fYear :
2009
fDate :
10-12 June 2009
Firstpage :
2940
Lastpage :
2945
Abstract :
A very successful scheme to accomplish trajectory tracking of unknown nonlinear systems consists of identifying the unknown dynamics using differential neural networks and on the basis of the so obtained mathematical model to develop an appropriate control law. The purpose of this paper is to present some new results in this sense. In particular, for the neural identifier, a new online learning law which permits to guarantee the boundedness for both the weights and the identification error without using a dead zone function is showed. Likewise, based on this neural identifier, a new control law to guarantee the boundedness of the tracking error is developed. These results are proved using a Lyapunov like analysis. With respect to the approach based on the local optimal control theory, the new approach has a similar performance but its main advantage consists of simplifying considerably the design process. The workability of the suggested approach is illustrated by simulation.
Keywords :
Lyapunov methods; control system synthesis; learning (artificial intelligence); mathematical analysis; neurocontrollers; nonlinear control systems; optimal control; position control; tracking; Lyapunov analysis; controller design process; dead zone function; differential neural network; local optimal control theory; mathematical model; neural identifier; nonlinear system; online neural learning law; trajectory tracking error; Artificial neural networks; Automatic control; Function approximation; Mathematical model; Neural networks; Nonlinear control systems; Nonlinear systems; Optimal control; Riccati equations; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2009. ACC '09.
Conference_Location :
St. Louis, MO
ISSN :
0743-1619
Print_ISBN :
978-1-4244-4523-3
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2009.5160014
Filename :
5160014
Link To Document :
بازگشت