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任意初态下非线性不确定系统的迭代学习控制

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任意初态下非线性不确定系统的迭代学习控制 李国军1,2, 陈东杰2, 韩一士2, 许中石21. 浙江工业大学信息工程学院, 杭州 310023;
2. 浙江警察学院公共基础部, 杭州 310053 Iterative Learning Control with Arbitrary Initial States for Nonlinear Systems LI Guojun1,2, CHEN Dongjie2, HAN Yishi2, XU Zhongshi21. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China;
2. Basic Courses Department, Zhejiang Police College, Hangzhou 310053, China
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摘要本文针对带有任意初态偏差的非线性不确定系统,提出了一种新的控制算法.在控制过程中,系统在某个指定时间内一次只修正一个初态偏差,当上一个初态偏差修正操作完成以后再开始下一个初态偏差的修正,最终实现所有任意初态偏差的完全修正,并且该方法能在某个指定区间实现对目标的完全跟踪.最后的仿真结果验证了算法的有效性.
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收稿日期: 2018-06-13
PACS:O231.7
基金资助:浙江省自然科学基金(No.LQ18G010001)和北京东方计量测试研究所刘尚合院士专家工作站静电研究基金(No.BOIMTLSHJD20182001)资助项目.

引用本文:
李国军, 陈东杰, 韩一士, 许中石. 任意初态下非线性不确定系统的迭代学习控制[J]. 应用数学学报, 2019, 42(4): 455-469. LI Guojun, CHEN Dongjie, HAN Yishi, XU Zhongshi. Iterative Learning Control with Arbitrary Initial States for Nonlinear Systems. Acta Mathematicae Applicatae Sinica, 2019, 42(4): 455-469.
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[1] Arimoto S, Kawamura S. Bettering operation of robots by learning. J. Robotic Syst., 1984, 2(1):123-140
[2] Bristow D, Tharayil M, Alleyne A. A survey of iterative learning control. IEEE Control Syst. Mag., 2006, 3(26):96-114
[3] Ishihara T, Abe K, Takeda H. A discrete-time design of robust iterative learning controllers. IEEE Trans. Syst. Man Cy. B, 1992, 1(22):74-84
[4] Saab S S, Vogt W G, Mickle M H. Learning control algorithms for tracking ‘slowly’ varying trajectories. IEEE Trans. Syst. Man Cy. B, 1997, 4(27):657-670
[5] Heinzinger G, Fenwick D, Paden B, Miyazaki F. Stability of learning control with disturbances and uncertain initial conditions. IEEE Trans. Autom. Control, 1992, 1(37):110-114
[6] Wang D. Convergence and robustness of discrete time nonlinear systems with iterative learning control. Automatica, 1998, 11(34):1445-1448
[7] Arimoto S. Learning control theory for robotic motion. Int. J. Adapt. Control Signal Processing, 1990, 6(4):543-564
[8] Lee H, Bien Z. Study on robustness of iterative learning control with nonzero initial error. Int. J. Control, 1996, 3(64):345-359
[9] Park K, Bien Z, Hwang D. A study on the robustness of a PID-type iterative learning controller against initial state error. Int. J. Syst. Sci., 1999, 1(30):49-59
[10] Sun M, Wang D. Initial condition issues on iterative learning control for nonlinear systems with time delay. Int. J. Syst. Sci., 2001, 11(32):1365-1375
[11] Sun M, Wang D. Closed-loop iterative learning control for nonlinear systems with initial shifts. Int. J. Adapt. Control Signal Processing, 2002, 7(16):515-538
[12] Sun M, Wang D. Iterative learning control with initial rectifying action. Automatica, 2002, 7(38):1177-1182
[13] Li X, Chow T, Ho J, Zhang J. Iterative learning control with initial rectifying action for nonlinear continuous systems. IET Control Theory Appl., 2009, 1(3):49-55
[14] Xu J, Tan Y. A composite energy function-based learning control approach for nonlinear systems with time-varying parametric uncertainties. IEEE Trans. Autom. Control, 2002, 11(47):1940-1945
[15] Qu Z, Xu J. Asymptotic learning control for a class of cascaded nonlinear uncertain systems. IEEE Trans. Autom. Control, 2002, 8(47):1369-1376
[16] Tayebi A, Chien C. A unified adaptive iterative learning control framework for uncertain nonlinear systems. IEEE Trans. Autom. Control, 2007, 10(52):1907-1913
[17] Chien C, Hsu C, Yao C. Fuzzy system-based adaptive iterative learning control for nonlinear plants with initial state errors. IEEE Trans. Fuzzy Syst., 2004, 5(12):724-732
[18] 孙明轩. 有限时间迭代学习控制. 系统科学与数学, 2010, 6(30):733-741(Sun M. Finite-time iterative learning control. Journal of Systems Science and Mathematical Sciences, 2010, 6(30):733-741)
[19] 谢华英, 孙明轩. 有限时间死区修正迭代学习控制器的设计. 控制理论与应用, 2009, 11(26):1225-1231(Xie H, Sun M. Design of iterative learning controllers with finite-time dead-zone modification. Control Theory & Applications, 2009, 11(26):1225-1231)
[20] 齐丽强, 孙明轩, 管海娃. 非参数不确定系统的有限时间迭代学习控制. 自动化学报, 2014, 7(40):1320-1327(Qi L, Sun M, Guan H. Finite-time Iterative Learning Control for Systems with Nonparametric Uncertainties. Acta Automatica Sinica, 2014, 7(40):1320-1327)
[21] Chi R, Hou Z, Xu J. Adaptive ILC for a class of discrete-time systems with iteration-varying trajectory and random initial condition. Automatica, 2008, 8(44):2207-2213
[22] Xu J, Xu J. On Iterative Learning from Different Tracking tasks in the presence of time-varying uncertainties. IEEE Trans. Syst. Man Cy. B, 2004, 1(34):589-597
[23] Yin C, Xu J, Hou Z. A high-order internal model based iterative learning control scheme for nonlinear systems with time-iteration-varying parameters. IEEE Trans. Autom. Control, 2010, 55(11):2665-2670
[24] Marino R, Tomei P. An iterative learning control for a class of partially feedback linearizable systems. IEEE Trans. Autom. Control, 2009, 8(54):1991-1996
[25] 陈彭年, 秦化淑, 方学毅. 控制增益时变的非线性系统的迭代学习控制. 系统科学与数学, 2012, 6(32):693-704(Chen P, Qin H, Fang X. Iterative learning control for uncertain nonlinear systems with time-varying control gain. Journal of Systems Science and Mathematical Sciences, 2012, 6(32):693-704)

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