Adaptive neural control of SISO non-affine nonlinear time-delay systems with unknown hysteresis input

Author

Ren, Beibei ; Ge, Shuzhi Sam ; Lee, Tong Heng ; Su, Chun-Yi

Author_Institution

Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore

fYear

2008

fDate

11-13 June 2008

Firstpage

4203

Lastpage

4208

Abstract

In this paper, adaptive neural control is investigated for a class of SISO unknown non-affine nonlinear systems with state time-varying delays and unknown hysteresis input. The non-affine problem is solved by adopting mean value theorem and implicit function theorem. The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The effect of the unknown hysteresis with the Prandtl-Ishlinskii model is also mitigated through the proposed adaptive control. By utilizing the Lyapunov synthesis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB).

Keywords

Lyapunov methods; adaptive control; closed loop systems; delays; hysteresis; neurocontrollers; nonlinear control systems; time-varying systems; Lyapunov-Krasovskii functionals; Prandtl-Ishlinskii model; SISO; adaptive neural control; closed-loop control system; hysteresis input; nonaffine nonlinear time-delay systems; semiglobally uniformly ultimately bounded; state time-varying delays; Adaptive control; Control system synthesis; Control systems; Delay; Hysteresis; Nonlinear control systems; Nonlinear systems; Programmable control; Time varying systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2008

Conference_Location

Seattle, WA

ISSN

0743-1619

Print_ISBN

978-1-4244-2078-0

Electronic_ISBN

0743-1619

Type

conf

DOI

10.1109/ACC.2008.4587153

Filename

4587153