Title :
Adaptive output feedback tracking control for nonaffine nonlinear systems
Author :
Esfandiari, Kasra ; Abdollahi, Farzaneh ; Talebi, Heidar Ali
Author_Institution :
Dept. of Electr. Eng., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
This paper focuses on adaptive output feedback tracking control of nonlinear systems, in which the functions of system are unknown. A two-layered feedforward Neural Network (NN) is employed to approximate the desired control signal. In order to estimate system states, an NN-based high gain observer is introduced, which does not suffer from peaking phenomenon. Also, the stability analysis of the overall system is provided based on the non-separation principle. As compared to most of the previous approaches which concentrate on affine systems, the presented method is applicable to nonaffine nonlinear systems. Furthermore, the presented method does not rely on having a lot of a priori knowledge about the system dynamics, the corresponding adaption laws are simple, easy to implement and reliable. Finally, simulation results are presented to verify the significant potential of the proposed controller.
Keywords :
adaptive control; affine transforms; feedback; feedforward neural nets; neurocontrollers; nonlinear control systems; observers; stability; tracking; NN-based high gain observer; adaption law; adaptive output feedback tracking control; affine system; control signal; nonaffine nonlinear system; nonseparation principle; overall system; peaking phenomenon; stability analysis; system dynamics; system state estimation; two-layered feedforward neural network; Approximation methods; Artificial neural networks; Nonlinear systems; Observers; Output feedback; Stability analysis; Trajectory;
Conference_Titel :
Electrical Engineering (ICEE), 2015 23rd Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4799-1971-0
DOI :
10.1109/IranianCEE.2015.7146353