Adaptive iterative learning control for a class of parameterized fractional-order systems subjected to backlash-like hysteresis

被引:0
|
作者
Wang, Hong [1 ]
Wei, Jianming [2 ,3 ]
Wang, Zhe [2 ]
机构
[1] Naval Aviat Univ, Yantai, Peoples R China
[2] Naval Univ Engn, Wuhan, Peoples R China
[3] Naval Univ Engn, Wuhan 430033, Peoples R China
关键词
Adaptive iterative learning control; parameterized fractional-order systems; backlash-like hysteresis; Mittag-Leffler function; boundary layer function; frequency distributed model; NONLINEAR-SYSTEMS; BACKSTEPPING CONTROL;
D O I
10.1177/09596518231208221
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 article, a fractional-order adaptive iterative learning control scheme is proposed for a class of parameterized fractional-order systems with unknown control gain and backlash-like hysteresis nonlinearity under disturbance. Based on the sufficient condition for the stability of linear fractional-order systems, a sliding mode surface of tracking errors is constructed to facilitate the controller design and stability analysis. A new boundary layer function is designed by using Mittag-Leffler function to relax the restriction of the identical initial condition of iterative learning control design. The fractional-order differential-type adaptive laws and difference-type learning law are designed to estimate unknown constant parameters and time-varying parameter, respectively. To deal with the influence of backlash-like hysteresis nonlinearity reminder term and unknown bounded external disturbance, a robust control term is designed by employing the hyperbolic tangent function with a convergent series sequence which can guarantee the learning convergence along iteration axis. By constructing Lyapunov-like composite energy function, the stability analysis is presented to prove the convergence of the system output to a small neighborhood of the desired trajectory and the boundedness of all the closed-loop signals. Finally, a simulation example of second-order nonlinear fractional-order system is presented, which demonstrates the effectiveness of the proposed fractional-order adaptive iterative learning control scheme.
引用
收藏
页码:410 / 424
页数:15
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