Title :
NN-Based Adaptive Tracking Control of Uncertain Nonlinear Systems Disturbed by Unknown Covariance Noise
Author :
Psillakis, Haris E. ; Alexandridis, Antonio T.
Author_Institution :
Univ. of Patras, Rion
Abstract :
A class of uncertain nonlinear systems that are additionally driven by unknown covariance noise is considered. Based on the backstepping technique, adaptive neural control schemes are developed to solve the output tracking control problem of such systems. As it is proven by stability analysis, the proposed controller guarantees that all the error variables are bounded with desired probability in a compact set while the tracking error is mean-square semiglobally uniformly ultimately bounded (M-SGUUB). The tracking performance and the effectiveness of the proposed design are evaluated by simulation results.
Keywords :
adaptive control; covariance analysis; error statistics; neurocontrollers; nonlinear control systems; probability; stability; tracking; uncertain systems; NN-based adaptive tracking control; backstepping technique; compact set; error statistics; neural control; output tracking control; probability; stability; uncertain nonlinear system; unknown covariance noise; Adaptive control; neural networks (NNs); uncertain stochastic nonlinear systems;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2007.901274
