DocumentCode
2130608
Title
A neural network type feedback law for linear systems with position and rate limited actuators
Author
Rouhani, Modjtaba ; Menhaj, Mohammad B.
Author_Institution
Azad Islamic Univ., Gonabad
fYear
2008
fDate
4-7 May 2008
Abstract
This paper introduces a novel nonlinear feedback for locally stabilizing a class of multi-input nonlinear systems consist of a linear system together with saturated and rate limited actuators. No assumption is made on the stability of the linear system. The structure of the proposed nonlinear system is of a ldquoNeural Network Typerdquo. The Neural network feedback law is designed to achieve the greatest ellipsoid domain of stability of closed loop system.
Keywords
actuators; closed loop systems; control system synthesis; feedback; linear systems; neurocontrollers; nonlinear control systems; stability; closed loop system stability; ellipsoid domain; linear saturated system; multiinput nonlinear system; neural network type nonlinear feedback law design; position limited actuator; rate limited actuator; Hydraulic actuators; Linear systems; Neural networks; Neurofeedback; Neural Networks; linear saturated systems; nonlinear control; rate limit;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
Conference_Location
Niagara Falls, ON
ISSN
0840-7789
Print_ISBN
978-1-4244-1642-4
Electronic_ISBN
0840-7789
Type
conf
DOI
10.1109/CCECE.2008.4564588
Filename
4564588
Link To Document