Output-feedback robust adaptive control for strict-feedback stochastic nonlinear systems under inverse optimality costs

Author

Wang, Jingsheng ; Wang, Jun ; Liu, Wei ; Ji, Ping

Author_Institution

Key Lab. of Machine Vision & Intell. Control Technol., Hefei Univ., Hefei, China

fYear

2010

fDate

26-28 May 2010

Firstpage

3507

Lastpage

3512

Abstract

The solvable problem of adaptive inverse optimal stabilization in probability is discussed, and control laws of global asymptotic stability in probability and adaptive inverse optimal stabilization in probability are developed for output-feedback stochastic nonlinear continuous systems with additive standard Wiener noises and constant unknown parameters by using Itô´s differentiation rule and adaptive backstepping algorithms. The adaptive control law and the parameter update laws can be obtained at same time by this design scheme.

Keywords

adaptive control; asymptotic stability; continuous systems; differentiation; feedback; nonlinear control systems; optimal control; probability; robust control; stochastic systems; Ito differentiation rule; adaptive backstepping algorithm; adaptive inverse optimal stabilization; additive standard Wiener noise; global asymptotic stability; output-feedback robust adaptive control; stochastic nonlinear continuous system; strict-feedback stochastic nonlinear system; Adaptive control; Control systems; Cost function; Nonlinear control systems; Nonlinear systems; Optimal control; Programmable control; Robust control; Stochastic resonance; Stochastic systems; Backstepping algorithm; Inverse optimality; Output-feedback; Stability in probability; Wiener noises;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5498545

Filename

5498545