Journal of Pure and Applied Mathematics: Advances and Applications[1] S. Arimoto, S. Kawamura and F. Miyazaki, Bettering operation of
robots by learning, Journal of Robotic Systems 1(2) (1984),
123-140.
DOI: https://doi.org/10.1002/rob.4620010203
[2] H. S. Lee and Z. Bien, A note on convergence property of iterative
learning controller with respect to sup norm, Automatica 33(8) (1997),
1591-1593.
DOI: https://doi.org/10.1016/S0005-1098(97)00068-X
[3] Y. Chen, Z. Gong and C. Wen, Analysis of a high-order iterative
learning control algorithm for uncertain nonlinear systems with state
delays, Automatica 34(3) (1998), 345-353.
DOI: https://doi.org/10.1016/S0005-1098(97)00196-9
[4] Sheng Liu, Changkui Xu and Lanyong Zhang, Robust course keeping
control of a fully submerged hydrofoil vessel without velocity
measurement: An iterative learning approach, Mathematical Problems in
Engineering (2017); Article ID 7979438, 14 pages.
DOI: https://doi.org/10.1155/2017/7979438
[5] Dongqi Ma and Hui Lin, An accelerating iterative learning control
based on an adjustable learning interval, Journal of Control Science
and Engineering (2017); Article ID 1731676, 6 pages.
DOI: https://doi.org/10.1155/2017/1731676
[6] R. H. Chi, Z. S. Hou and J. X. Xu, Adaptive ILC for a class of
discrete-time systems with iteration-varying trajectory and random
initial condition, Automatica 44(8) (2008), 2207-2213.
DOI: https://doi.org/10.1016/j.automatica.2007.12.004
[7] Leila Noueili, Wassila Chagra and Moufida Ksouri, New iterative
learning control algorithm using learning gain based on 
inversion for nonsquare multi-input
multi-output systems, Modelling and Simulation in Engineering (2018);
Article ID 4195938, 9 pages.
DOI: https://doi.org/10.1155/2018/4195938
[8] Lei Li, Lebesgue-p norm convergence analysis of 
iterative learning control for fractional-order
nonlinear systems, Discrete Dynamics in Nature and Society (2018);
Article ID 5157267, 10 pages.
DOI: https://doi.org/10.1155/2018/5157267
[9] Xiongfeng Deng, Xiuxia Sun and Shuguang Liu, Consensus learning
control for leader-following nonlinear multiagent systems with control
delay, Wireless Communications and Mobile Computing (2019); Article ID
2035683, 10 pages.
DOI: https://doi.org/10.1155/2019/2035683
[10] Xiongfeng Deng, Xiuxia Sun, Shuguang Liu and Boyang Zhang,
Leader-following consensus for second-order nonlinear multiagent
systems with input saturation via distributed adaptive neural network
iterative learning control, Complexity (2019); Article ID 9858504, 13
pages.
DOI: https://doi.org/10.1155/2019/9858504
[11] Xiaoli Li, Jian Liu, Linkun Wang, Kang Wang and Yang Li, Welding
process tracking control based on multiple model iterative learning
control, Mathematical Problems in Engineering (2019); Article ID
6137352, 9 pages.
DOI: https://doi.org/10.1155/2019/6137352
[12] J. Li and J. Li, Iterative learning control approach for a kind
of heterogeneous multi-agent systems with distributed initial state
learning, Applied Mathematics and Computation 265 (2015),
1044-1057.
DOI: https://doi.org/10.1016/j.amc.2015.06.035
[13] L. Yan and J. Wei, Fractional order nonlinear systems with delay
in iterative learning control, Applied Mathematics and Computation 257
(2015), 546-552.
DOI: https://doi.org/10.1016/j.amc.2015.01.014
[14] H. Cai, Y. Huang, J. Du, T. Tang, D. Zuo and J. Li, Iterative
learning control with extended state observer for telescope system,
Mathematical Problems in Engineering (2015); Article ID 701510, 8
pages.
DOI: http://dx.doi.org/10.1155/2015/701510
[15] Zhang Qunli, The effect of initial state error for nonlinear
systems with delay via iterative learning control, Advances in
Mathematical Physics (2016); Article ID 4619450, 6 pages.
DOI: http://dx.doi.org/10.1155/2016/4619450
[16] J. Cao and Y. Wan, Matrix measure strategies for stability and
synchronization of inertial BAM neural network with time delay, Neural
Networks 53 (2014), 165-172.
DOI: https://doi.org/10.1016/j.neunet.2014.02.003
[17] S. Das, A. Acharya and I. Pan, Simulation studies on the design
of optimum PID controller to suppress chaotic oscillations in a family
of Lorenz-like multi-wing attractors, Mathematics and Computers in
Simulation 100 (2014), 72-87.
DOI: https://doi.org/10.1016/j.matcom.2014.03.002
[18] C. Yi, Y. Zhang and D. Guo, A new type of recurrent neural
networks for real-time solution of Lyapunov equation with time-varying
coefficient matrices, Mathematics and Computers in Simulation 92
(2013), 40-52.
DOI: https://doi.org/10.1016/j.matcom.2013.04.019
[19] Y. Zhang, M. Li, Y. Yin, L. Jin and X. Yu, Controller design of
nonlinear system for fully trackable and partially trackable paths by
combining ZD and GD, in: Proceedings 25th Control and Decision
Conference (2013), 209-214.
DOI: https://doi.org/10.1109/CCDC.2013.6560922
[20] Y. Zhang, C. Yi, D. Guo and J. Zheng, Comparison on Zhang neural
dynamics and gradient-based neural dynamics for online solution of
nonlinear time-varying equation, Neural Computing and Applications
20(1) (2011), 1-7.
DOI: https://doi.org/10.1007/s00521-010-0452-y
[21] S. S. Ge, F. Hong and T. H. Lee, Robust adaptive control of
nonlinear systems with unknown time delays, Automatica 41(7) (2005),
1181-1190.
DOI: https://doi.org/10.1016/j.automatica.2005.01.011
[22] C. C. Hua, G. Feng and X. P. Guan, Robust controller design of a
class of nonlinear time delay systems via backstepping method,
Automatica 44(2) (2008), 567-573.
DOI: https://doi.org/10.1016/j.automatica.2007.06.008
[23] X. D. Ye, Adaptive stabilization of time-delay feedforward
nonlinear systems, Automatica 47(5) (2011), 950-955.
DOI: https://doi.org/10.1016/j.automatica.2011.01.006
[24] J. Na, Adaptive prescribed performance control of nonlinear
systems with unknown dead zone, International Journal of Adaptive
Control and Signal Processing 27(5) (2013), 426-446.
DOI: https://doi.org/10.1002/acs.2322
[25] Z. Y. Sun and Y. G. Liu, Adaptive control design for a class of
uncertain high-order nonlinear systems with time delay, Asian Journal
of Control 17(2) (2015), 535-543.
DOI: https://doi.org/10.1002/asjc.895
[26] Qunli Zhang, Synchronization of multi-chaotic systems via ring
impulsive control, Control Theory and Applications 27(2) (2010),
226-232.
[27] Qunli Zhang, Synchronization of multi-chaotic systems with ring
and chain intermittent connections, Applied Mechanics and Materials
241-244 (2013), 1081-1087.
DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.1081
[28] Q. Zhang, A class of vector Lyapunov functions for stability
analysis of nonlinear impulsive differential systems, Mathematical
Problems in Engineering (2014); Article ID 649012, 9 pages.
DOI: http://dx.doi.org/10.1155/2014/649012
[29] Q. Zhang, Matrix measure with application in quantized
synchronization analysis of complex networks with delayed time via the
general intermittent control, Applied Mathematics 4(10) (2013),
1417-1426.
DOI: http://dx.doi.org/10.4236/am.2013.410192
[30] M. X. Sun and B. J. Huang, Iterative Learning Control, National
Defense Industry Press, Beijing, China, 1999.
[31] R. P. Agarwal, S. Deng and W. Zhang, Generalization of a retarded
Gronwall-like inequality and its applications, Applied Mathematics and
Computation 165(3) (2005), 599-612.
DOI: https://doi.org/10.1016/j.amc.2004.04.067
[32] Y. Zhang, W. Ma and B. Cai, From Zhang neural network to Newton
iteration for matrix inversion, IEEE Transactions on Circuits and
Systems I: Regular Papers 56(7) (2009), 1405-1415.
DOI: https://doi.org/10.1109/TCSI.2008.2007065
[33] Y. Zhang and C. Yi, Zhang Neural Network and Neural-Dynamic
Method, Nova Science Publishers, New York, 2011.
