Iterative learning control with guaranteed transient performance

被引:2
作者
Guan, Hai-Wa [1 ,2 ]
Sun, Ming-Xuan [1 ]
Qi, Li-Qiang [1 ]
机构
[1] College of Information Engineering, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang
[2] Wenzhou Vocational College of Science and Technology, Wenzhou, 325006, Zhejiang
来源
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2014年 / 31卷 / 10期
关键词
Convergence; Iterative learning control; Transient performance; Uncertain nonlinear systems;
D O I
10.7641/CTA.2014.40199
中图分类号
学科分类号
摘要
For a class of uncertain nonlinear time-varying systems, we present an iterative learning control scheme guaranteeing transient performance bounds. By introducing an error transformation, we convert the problem of guaranteeing transient performance of the tracking error to that of ensuring boundedness of the transformed error. Applying Lyapunov synthesis, we carry out the control design for handling both parametric and nonparametric uncertainties of system dynamics. It is shown that, with the use of fully-saturated learning mechanisms, the system output can completely track the desired trajectory over the entire pre-specified time interval as the number of iteration increases, and the tracking error is confined within the transient performance bounds for each iteration cycle, while the boundedness and the uniform convergence of the transformed error are guaranteed. Simulation results are presented to demonstrate the effectiveness of this learning control method. ©, 2014, South China University of Technology. All right reserved.
引用
收藏
页码:1295 / 1301
页数:6
相关论文
共 22 条
[1]  
Arimoto S., Kawamura S., Miyazaki F., Bettering operation of robots by learning , Journal of Robotic Systems, 1, 2, pp. 123-140, (1984)
[2]  
Sadegh N., Horowitz R., Kao W.W., Et al., A unified approach to the design of adaptive and repetitive controllers for robotic manipulators , ASME Journal of Dynamic Systems, Measurement, and Control, 112, 4, pp. 618-629, (1990)
[3]  
Kuc T., Lee J.S., An adaptive learning control of uncertain robotic systems , Proceedings of the 30th IEEE Conference on Decision and Control, pp. 1206-1211, (1991)
[4]  
French M., Rogers E., Nonlinear iterative learning by an adaptive Lyapunov technique , International Journal of Control, 73, 10, pp. 840-850, (2000)
[5]  
Qu Z.H., Xu J.X., Asymptotic learning control for a class of cascaded nonlinear uncertain systems , IEEE Transactions on Automatic Control, 47, 8, pp. 1369-1376, (2002)
[6]  
Choi J.Y., Lee J.S., Adaptive iterative learning control of uncertain robotic system , IEE Procedings-Control Theory and Application, 147, 2, pp. 217-223, (2000)
[7]  
Sun M.X., Ge S.S., Adaptive repetitive control for a class of nonlinearly parametrzed systems , IEEE Transactions on Automatic Control, 51, 10, pp. 1684-1688, (2006)
[8]  
Marino R., Tomei P., An iterative learning control for a class of partially feedback linearizable systems , IEEE Transactions on Automatic Control, 54, 8, pp. 1991-1996, (2009)
[9]  
Xu J.X., Xu J., On iterative learning from different tracking tasks in the presence of time-varying uncertainties , IEEE Transactions on System, Man, and Cybernetics, Part B, 34, 1, pp. 589-597, (2004)
[10]  
Li J., Sun Y., Liu Y., Hybrid adaptive iterative learning control of non-uniform trajectory tracking , Control Theory & Applications, 25, 1, pp. 100-104, (2008)