References
- Ahn, H., Chen, Y., & Moore, K. L. (2006, October). Intermittent iterative learning control. In Proceedings of the IEEE International Symposium on Intelligent Control (pp. 832–837). IEEE.
- Ahn, H., Chen, Y., & Moore, K. L. (2007). Iterative learning control: Brief survey and categorization. IEEE Transactions on Systems, Man, and Cybernetics C: Applications and Reviews, 37(6), 1099–1121. https://doi.org/https://doi.org/10.1109/TSMCC.2007.905759
- Ahn, H., Moore, K., & Chen, Y. (2006, June). Kalman filter-augmented iterative learning control on the iteration domain. In Proceedings of the American Control Conference (pp. 250–255). IEEE.
- Ahn, H., Moore, K. L., & Chen, Y. (2007). Stability analysis of discrete-time iterative learning control systems with interval uncertainty. Automatica, 43(5), 892–902. https://doi.org/https://doi.org/10.1016/j.automatica.2006.11.020
- Ahn, H., Moore, K. L., & Chen, Y. (2008a, July). Discrete-time intermittent iterative learning controller with independent data dropouts. In Proceedings of 17th IFAC World Congress (pp. 12442–12447). Elsevier.
- Ahn, H., Moore, K. L., & Chen, Y. (2008b, December). Stability of discrete-time iterative learning control with random data dropouts and delayed controlled signals in networked control systems. In Proceedings of the IEEE International Conference of Control Automation, Robotics, and Vision (pp. 757–762). IEEE.
- Anderson, B. D. O., & Moore, J. B. (1979). Optimal filtering. Prentice-Hall.
- Arimoto, S., Kawamura, S., & Miyazaki, F. (1984). Bettering operation of robots by learning. Journal of Robotic Systems, 1(2), 123–140. https://doi.org/https://doi.org/10.1002/(ISSN)1097-4563
- Basin, M., Shi, P., & Soto, P. (2012). Mean-square data-based controller for nonlinear polynomial systems with multiplicative noise. Information Sciences, 195(1), 256–265. https://doi.org/https://doi.org/10.1016/j.ins.2012.01.028
- Bristow, D. A., Tharayil, M. L., & Alleyne, A. G. (2006). A survey of iterative learning control. IEEE Control Systems Magazine, 26(3), 96–114. https://doi.org/https://doi.org/10.1109/MCS.2006.1636313
- Hu, J., Wang, Z., Chen, D., & Alsaadi, F. E. (2016). Estimation, filtering and fusion for networked systems with network-induced phenomena: New progress and prospects. Information Fusion, 31(1), 65–75. https://doi.org/https://doi.org/10.1016/j.inffus.2016.01.001
- Hu, X., Hu, Y., & Xu, B. (2014). Generalised Kalman filter tracking with multiplicative measurement noise in a wireless sensor network. IET Signal Processing, 8(5), 467–474. https://doi.org/https://doi.org/10.1049/sil2.v8.5
- Huang, L., & Fang, Y. (2013). Convergence analysis of wireless remote iterative learning control systems with dropout compensation. Mathematical Problems in Engineering, 2013(1), 1–9. https://doi.org/https://doi.org/10.1155/2013/609284
- Huang, L., Fang, Y., & Wang, T. (2014). Method to improve convergence performance of iterative learning control systems over wireless networks in presence of channel noise. IET Control Theory and Applications, 8(3), 175–182. https://doi.org/https://doi.org/10.1049/cth2.v8.3
- Huang, L., Fang, Y., & Wang, T. (2015). Convergence analysis of wireless remote iterative learning control systems with channel noise. Asian Journal of Control, 17(6), 2374–2381. https://doi.org/https://doi.org/10.1002/asjc.1107
- Jin, Y., & Shen, D. (2018). Iterative learning control for nonlinear systems with data dropouts at both measurement and actuator sides. Asian Journal of Control, 20(4), 1624–1636. https://doi.org/https://doi.org/10.1002/asjc.v20.4
- Li, X., & Hou, X. (2020). Robust design of iterative learning control for a batch process described by 2D Roesser system with packet dropouts and time-varying delays. International Journal of Robust and Nonlinear Control, 30(3), 1–15. https://doi.org/https://doi.org/10.1002/rnc.4812
- Liu, J., & Ruan, X. (2016). Networked iterative learning control approach for nonlinear systems with random communication delay. International Journal of Systems Science, 47(16), 3960–3969. https://doi.org/https://doi.org/10.1080/00207721.2016.1165894
- Liu, J., & Ruan, X. (2017a). Networked iterative learning control design for discrete-time systems with stochastic communication delay in input and output channels. International Journal of Systems Science, 48(9), 1844–1855. https://doi.org/https://doi.org/10.1080/00207721.2017.1289567
- Liu, J., & Ruan, X. (2017b). Networked iterative learning control for discrete-time systems with stochastic packet dropouts in input and output channels. Advances in Difference Equations, 2017(1), 1–21. https://doi.org/https://doi.org/10.1186/1687-1847-2012-1
- Liu, J., & Ruan, X. (2018). Networked iterative learning control design for nonlinear systems with stochastic output packet dropouts. Asian Journal of Control, 20(3), 1077–1087. https://doi.org/https://doi.org/10.1002/asjc.v20.3
- Nguyen, D. H., & Banjerdpongchai, D. (2011). A convex optimization design of robust iterative learning control for linear systems with iteration-varying parametric uncertainties. Asian Journal of Control, 13(1), 75–84. https://doi.org/https://doi.org/10.1002/asjc.266
- Owens, D. H., & Liu, S. (2011). Iterative learning control: quantifying the effect of output noise. IET Control Theory and Applications, 5(2), 379–388. https://doi.org/https://doi.org/10.1049/iet-cta.2009.0320
- Pan, Y., Marquez, H. J., Chen, T., & Sheng, L. (2009). Effects of network communications on a class of learning controlled nonlinear systems. International Journal of Systems Science, 40(7), 757–767. https://doi.org/https://doi.org/10.1080/00207720902957244
- Park, K., & Bien, Z. (2000). A generalized iterative learning controller against initial state error. International Journal of Control, 73(10), 871–881. https://doi.org/https://doi.org/10.1080/002071700405851
- Quevedo, D. E., Ahlen, A., & Johansson, K. H. (2013). State estimation over sensor networks with correlated wireless fading channels. IEEE Transactions on Automatic Control, 58(3), 581–593. https://doi.org/https://doi.org/10.1109/TAC.2012.2212515
- Saab, S. S. (2001). A discrete-time stochastic learning control algorithm. IEEE Transactions on Automatic Control, 46(6), 877–887. https://doi.org/https://doi.org/10.1109/9.928588
- Saab, S. S. (2005). Optimal selection of the forgetting matrix into an iterative learning control algorithm. IEEE Transactions on Automatic Control, 50(12), 2039–2043. https://doi.org/https://doi.org/10.1109/TAC.2005.860232
- Shen, D., Jin, Y., & Xu, Y. (2017). Learning control for linear systems under general data dropouts at both measurement and actuator sides: A Markov chain approach. Journal of the Franklin Institute, 354(13), 5091–5109. https://doi.org/https://doi.org/10.1016/j.jfranklin.2017.05.024
- Shen, D., & Qu, G. (2020). Performance enhancement of learning tracking systems over fading channels with multiplicative and additive randomness. IEEE Transactions on Neural Networks and Learning Systems, 31(4), 1196–1210. https://doi.org/https://doi.org/10.1109/TNNLS.5962385
- Shen, D., & Xu, J. (2017). A novel Markov chain based ILC analysis for linear stochastic systems under general data dropouts environments. IEEE Transactions on Automatic Control, 62(11), 5850–5857. https://doi.org/https://doi.org/10.1109/TAC.2016.2638044
- Son, T. D., Pipeleers, G., & Swevers, J. (2016). Multi-objective iterative learning control using convex optimization. European Journal of Control, 33(1), 35–42. https://doi.org/https://doi.org/10.1016/j.ejcon.2016.10.001
- Song, X., & Ju, H. P. (2017). Linear optimal estimation for discrete-time measurement delay systems with multichannel multiplicative noise. IEEE Transactions on Circuits and Systems II: Express Briefs, 64(2), 156–160. https://doi.org/https://doi.org/10.1109/TCSII.2016.2551548
- Wang, D. (1998). Convergence and robustness of discrete time nonlinear systems with iterative learning control. Automatica, 34(11), 1445–1448. https://doi.org/https://doi.org/10.1016/S0005-1098(98)00098-3
- Wang, X., Fu, M., & Zhang, H. (2012). Target tracking in wireless sensor networks based on the combination of KF and MLE using distance measurements. IEEE Transactions on Mobile Computing, 11(4), 567–576. https://doi.org/https://doi.org/10.1109/TMC.2011.59
- You, K., Li, Z., Quevedo, D. E., & Lewis, F. L. (2014). Recent developments in networked control and estimation. IET Control Theory and Applications, 8(18), 2123–2125. https://doi.org/https://doi.org/10.1049/cth2.v8.18
- You, K., & Xie, L. (2013). Survey of recent progress in networked control systems. Acta Automatica Sinica, 39(2), 101–117. https://doi.org/https://doi.org/10.1016/S1874-1029(13)60013-0
- Zhang, X. (2004). Matrix analysis and applications. Tsinghua Univ. Press.
- Zou, L., Wang, Z., Dong, H., & Han, Q. (2020). Moving horizon estimation with multirate measurements and correlated noises. International Journal of Robust and Nonlinear Control, 30(17), 7429–7445. https://doi.org/https://doi.org/10.1002/rnc.v30.17
- Zou, L., Wang, Z., Han, Q., & Zhou, D. (2019). Moving horizon estimation for networked time-delay systems under round-robin protocol. IEEE Transactions on Automatic Control, 64(12), 5191–5198. https://doi.org/https://doi.org/10.1109/TAC.9
- Zou, L., Wang, Z., Hu, J., & Zhou, D. (2020). Moving horizon estimation with unknown inputs under dynamic quantization effects. IEEE Transactions on Automatic Control, 65(12), 5368–5375. https://doi.org/https://doi.org/10.1109/TAC.9