Adaptive output feedback tracking control of stochastic nonlinear systems with dynamic uncertainties

Abstract

SummaryIn this paper, adaptive output feedback tracking control is developed for a class of stochastic nonlinear systems with dynamic uncertainties and unmeasured states. Neural networks are used to approximate the unknown nonlinear functions. K‐filters are designed to estimate the unmeasured states. An available dynamic signal is introduced to dominate the unmodeled dynamics. By combining dynamic surface control technique with backstepping, the condition in which the approximation error is assumed to be bounded is avoided. Using It ô formula and Chebyshev's inequality, it is shown that all signals in the closed‐loop system are bounded in probability, and the error signals are semi‐globally uniformly ultimately bounded in mean square or the sense of four‐moment. Simulation results are provided to illustrate the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd.

Adaptive tracking control for a class of non-affine switched stochastic nonlinear systems with unmodeled dynamics

“…It is a very common assumption in the existing literatures [3,39] and plays an instrumental role in dealing with stochastic inverse dynamics of system (1).…”

“…The objective of this paper is to design an adaptive controller for system (1) such that the output y follows the specified desired trajectory y r .…”

“…Recently, adaptive control for stochastic nonlinear systems have become a hot research topic, and a great number of results in this field have been reported [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. For example, some studies have been carried out for stochastic nonlinear systems combining K-filters with dynamic surface technique [1][2][3][4].…”

“…For example, some studies have been carried out for stochastic nonlinear systems combining K-filters with dynamic surface technique [1][2][3][4]. The issues of stochastic disturbance attenuation and asymptotic stabilization via output feedback for stochastic nonlinear systems with dynamical uncertainties were investigated in [5][6][7][8][9].…”

Adaptive finite-time tracking control for a class of switched nonlinear systems with unmodeled dynamics

“…Therefore, how to handle unmodeled dynamics is a meaningful topic when one investigates the system stability. Generally speaking, unmodeled dynamics include state unmodeled dynamics [5,6,15,20,[25][26][27][28][29][30][31][32] and input unmodeled dynamics [33][34][35][36][37][38]. State unmodeled dynamics denote the parts of invalid modeling during the parameterization, a few approaches were proposed to handle the adverse effects caused by them.…”