AILC for Nonlinearly Parameterized Systems with Unknown Distributed Time-Varying Delays and Unknown Control Direction
This paper addresses a new adaptive iterative learning control (AILC) approach for a class of nonlinear parameterized systems with unknown distributed time-varying delays and unknown control direction. By using the parameter separation technique combined with the signal replacement mechanism, a novel adaptive control strategy is designed to ensure the tracking error converging to zero on a finite time-interval in the mean-square sense. Simultaneously, Nussbaum-type function is used to detect the unknown control direction. The stability of the tracking error is also proven by constructing a Lyapunov-Krasovskii-like composite energy function (CEF). Two simulations example are presented to illustrate the effectiveness of the proposed control algorithms.
nonlinearly parameterized systems AILC distributed time-varying delays unknown control direction
Tang Shu Li Jun-min
School of science, Xidian University, Xi’an 710071, China
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
2960-2965
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）