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

被引：3
|
作者：
Ren, Beibei [1 ]
Ge, Shuzhi Sam [1 ]
Lee, Tong Heng [1 ]
Su, Chun-Yi [2 ]
机构：
[1] Natl Univ Singapore, Social Robot Lab, Interact Digital Media Inst, Singapore 117576, Singapore
[2] Concordia Univ, Dept Mech & Ind Engn, Montreal, PQ H3G 1M8, Canada
来源：
2008 AMERICAN CONTROL CONFERENCE, VOLS 1-12 | 2008年
关键词：
D O I：
10.1109/ACC.2008.4587153
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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 dosed-loop control system is proved to be semi-globally uniformly ultimately bounded (SGUUB).
引用
收藏
页码：4203 / +
页数：2
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