加速抑制随机初态误差影响的迭代学习控制

吕庆; 方勇纯; 任逍

doi:10.3724/SP.J.1004.2014.01295

加速抑制随机初态误差影响的迭代学习控制

doi: 10.3724/SP.J.1004.2014.01295

1.
南开大学机器人与信息自动化研究所天津 300071

基金项目:

国家自然科学基金（61127006，61325017）资助

详细信息

作者简介:
吕庆南开大学机器人与信息自动化研究所博士研究生. 主要研究方向为迭代学习控制及其在原子力显微镜中的应用. E-mail：lvq@robot.nankai.edu.cn

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- 文章访问数: 1884
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- PDF下载量: 826
- 被引次数: 0
出版历程
- 收稿日期: 2013-07-19
- 修回日期: 2013-12-16
- 刊出日期: 2014-07-20

Iterative Learning Control for Accelerated Inhibition Effect of Initial State Random Error

1.
Institute of Robotics and Automatic Information System, Nankai University, Tianjin 300071

Funds:

Supported by National Natural Science Foundation of China (61127006, 61325017)

摘要

摘要: 针对一类具有不确定性的多输入多输出非线性系统，提出一种迭代学习控制算法.该算法具有的特点是：针对任意初态情形，结合开环 D型迭代学习控制器的优点，在时间轴上设计了一个随迭代次数增加而缩短的时间段.在该时间段上，控制算法对状态偏差进行修正，以使系统输出在此段时间后跟踪期望输出，且系统跟踪误差收敛到一个界内.这个界仅由系统自身不确定性和不确定的外界干扰决定，与初态误差无关.当外界扰动为0，以及迭代次数趋于无穷时，经过上述时间段后，系统输出精确跟踪期望输出.理论证明和仿真结果都说明了该算法的有效性.
- 迭代学习控制 /
- 初始状态误差 /
- 快速学习 /
- 收敛性 /
- 鲁棒性
Abstract: A novel iterative learning control technique is presented for a class of multi-input and multi-output nonlinear systems with uncertainty. It is well known that the system output cannot track the desired output accurately and immediately due to the initial state error. In this paper, a special time interval, with the characteristics of more iterations and less time interval, is designed. By combining an open-loop D-type iterative learning controller, the random state errors are rectified in the special time interval. Subsequently, system outputs track the reference trajectory. Uniform bounds for the final tracking errors are obtained, which are only dependent on the system uncertainties and disturbances but independent of the initial errors. After the special time interval, the system outputs will accurately track desired outputs with infinite iteration and without disturbances. Both theoretical proof and simulation results show the effectiveness of the proposed algorithm.
- Iterative learning control /
- initial state error /
- fast learning /
- convergence /
- robustness

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参考文献(25)

[1]	Huang S N, Tan K K, Lee T H. Necessary and sufficient condition for convergence of iterative learning algorithm. Automatica, 2002, 38(7): 1257-1260
[2]	Li X D, Chow T W S, Ho J K L. 2-D system theory based iterative learning control for linear continuous systems with time-delays. IEEE Transactions on Circuits and Systems, 2005, 52(7): 1421-1430
[3]	Jiang P, Chen H D, Bamforth L C A. A universal iterative learning stabilizer for a class of MIMO systems. Automatica, 2006, 42(6): 973-981
[4]	Bu X H, Yu F S, Hou Z S, Yang H Z. Robust iterative learning control for nonlinear systems with measurement disturbances. Journal of Systems Engineering and Electronics, 2012, 23(6): 906-913
[5]	Li X D, Chow T W S, Ho J K L. Iterative learning control for linear time-variant discrete systems based on 2-D system theory. IEE Proceedings Control Theory and Application, 2005, 152(1): 13-18
[6]	Huang D Q, Xu J X. Steady-state iterative learning control for a class of nonlinear PDE processes. Journal of Process Control, 2011, 21(8): 1155-1163
[7]	Zhang Yu-Dong, Fang Yong-Chun. Learning control for systems with saturated output. Acta Automatica Sinica, 2011, 37(1): 92-98(张玉东, 方勇纯. 一类输出饱和系统的学习控制算法研究. 自动化学报, 2011, 37(1): 92-98)
[8]	Zhang J, Yemashov S, Pantelelis N G. Iterative learning control of a reactive polymer composite moulding process. Procedia Engineering, 2012, 42: 1100-1105
[9]	Wang L M, Mo S Y, Zhou D H, Gao F R, Chen X. Delay-range-dependent robust 2D iterative learning control for batch processes with state delay and uncertainties. Journal of Process Control, 2013, 23(5): 715-730
[10]	Sun M X, Wang D W. Closed-loop iterative learning control for non-linear systems with initial shifts. International Journal of Adaptive Control and Signal Processing, 2002, 16(7): 515-538
[11]	Chi R H, Zhang D X, Liu X M, Hou Z S, Jin S T. An anticipatory terminal iterative learning control approach with applications to constrained batch processes. Chinese Journal of Chemical Engineering, 2013, 21(3): 271-275
[12]	Lee K H, Bien Z. Initial condition problem of learning control. IEE Proceedings Control Theory and Application, 1991, 138(6): 525-528
[13]	Heinzinger G, Fenwick D, Paden B, Miyazaki F. Stability of learning control with disturbances and uncertain initial conditions. IEEE Transactions on Automatic Control, 1992, 37(1): 110-114
[14]	Wang D W. Convergence and robustness of discrete time nonlinear systems with iterative learning control. Automatica, 1998, 34(11): 1145-1148
[15]	Sun M X, Wang D W. Iterative learning control with initial rectifying action. Automatica, 2002, 38(7): 1177-1182
[16]	Park K H. An average operator-based PD-type iterative learning control for variable initial state error. IEEE Transactions on Automatic Control, 2005, 50(6): 865-869
[17]	Zhang J, Chow T W S, Ho J K L, Li X D. Iterative learning control with initial rectifying action for nonlinear continuous systems. IET Control Theory and Applications, 2009, 3(1): 49-55
[18]	Sun Ming-Xuan, Huang Bao-Jian, Zhang Xue-Zhi. PD-type iterative learning control for a class of nonlinear systems. Acta Automatica Sinica, 1998, 24(5): 711-714(孙明轩, 黄宝健, 张学智. 非线性系统的PD型迭代学习控制. 自动化学报, 1998, 24(5): 711-714)
[19]	Chen Y Q, Wen C Y, Xu J X, Sun M X. An initial state learning method for iterative learning control of uncertain time-varying systems. In: Proceedings of the 35th Conference on Decision and Control. Kobe: IEEE, 1996. 3396-4001
[20]	Sun Ming-Xuan, Huang Bao-Jian. Iterative Learning Control. Beijing: National Defence Industry Press, 1999. 285-286(孙明轩, 黄宝健. 迭代学习控制. 北京: 国防工业出版社, 1999. 285-286)
[21]	Arimoto S, Kawamura S, Miyazaki F. Bettering operation of robots by learning. Journal of Robotic Systems, 1984, 1(2): 123-140
[22]	Han Jing-Qing. Active Disturbance Rejection Control Tech-Nique——the Technique for Estimating and Compensating the Uncertainties. Beijing: National Defence Industry Press, 2009. 46-110(韩京清. 自抗扰控制技术—估计补偿不确定因素的控制技术. 北京: 国防工业出版社, 2009. 46-110)
[23]	Sun M X, Wang D W, Wang Y Y. Varying-order iterative learning control against perturbed initial conditions. Journal of the Franklin Institute, 2010, 347(8): 1526-1549
[24]	Sun Ming-Xuan, Yan Qiu-Zhen. Error tracking of iterative learning control systems. Acta of Automatica Sinica, 2013, 39(3): 251-262 (孙明轩, 严求真. 迭代学习控制系统的误差跟踪设计方法. 自动化学报, 2013, 39(3): 251-262)
[25]	Sun Ming-Xuan, Li Zhi-Le, Zhu Sheng. Varying-order sam-pled-data iterative learning control for MIMO nonlinear systems. Acta Automatica Sinica, 2013, 39(7): 1027-1036 (孙明轩, 李芝乐, 朱胜. 多变量非线性系统的变阶采样迭代学习控制. 自动化学报, 2013, 39(7): 1027-1036)

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加速抑制随机初态误差影响的迭代学习控制

doi: 10.3724/SP.J.1004.2014.01295

作者简介:
吕庆南开大学机器人与信息自动化研究所博士研究生. 主要研究方向为迭代学习控制及其在原子力显微镜中的应用. E-mail：lvq@robot.nankai.edu.cn

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Iterative Learning Control for Accelerated Inhibition Effect of Initial State Random Error

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加速抑制随机初态误差影响的迭代学习控制

doi: 10.3724/SP.J.1004.2014.01295

作者简介: 吕庆 南开大学机器人与信息自动化研究所博士研究生. 主要研究方向为迭代学习控制及其在原子力显微镜中的应用. E-mail：lvq@robot.nankai.edu.cn

计量

出版历程

Iterative Learning Control for Accelerated Inhibition Effect of Initial State Random Error

计量

出版历程

目录

作者简介:
吕庆南开大学机器人与信息自动化研究所博士研究生. 主要研究方向为迭代学习控制及其在原子力显微镜中的应用. E-mail：lvq@robot.nankai.edu.cn