Title :
Output Feedback for a Class of Non-affine Nonlinear System via Neural Networks
Author :
Zhao Tong ; Zhao Pin
Author_Institution :
Dept. of Autom. Control, Qingdao Univ. of Sci. & Technol., Qingdao, China
Abstract :
An adaptive output feedback control scheme is proposed for a class of non-affine nonlinear system in which the output signal can track the reference signal. A state observer is constructed to estimate the unknown state in system. A three-layer neural network is introduced to compensate the modeling errors and a Robust control is also used to reduce the approximation error, which adds to the anti-interference ability of the system. The stability of the system is accurately proved. Simulation results demonstrate the effectiveness and feasibility of proposed scheme.
Keywords :
adaptive control; approximation theory; feedback; neurocontrollers; nonlinear control systems; observers; robust control; adaptive output feedback control scheme; anti-interference ability; approximation error; non affine nonlinear system; robust control; state observer; three-layer neural network; Adaptive control; Adaptive systems; Control systems; Neural networks; Nonlinear control systems; Nonlinear systems; Observers; Output feedback; Programmable control; State estimation; Non-affine nonlinear system; adaptive control; neural networks(NN); output feedback;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.161