Point-to-point iterative learning control with quantised input signal and actuator faults

References

• Arimoto, S., Kawamura, S., & Miyazaki, F (1984). Bettering operations of robots by learning. Journal of Robotic Systems, 1(2), 123–140. https://doi.org/10.1002/(ISSN)1097-4563
   Web of Science ®Google Scholar
• Bu, X., Wang, T., Hou, Z., & Chi, R (2015). Iterative learning control for discrete-time systems with quantised measurements. IET Control Theory Applications, 9(9), 1455–1460. https://doi.org/10.1049/cth2.v9.9
   Web of Science ®Google Scholar
• Chen, Y., Chu, B., & Freeman, C. T (2019a). A coordinate descent approach to optimal tracking time allocation in point-to-point ILC. Mechatronics, 59, 25–34. https://doi.org/10.1016/j.mechatronics.2019.02.005
   Web of Science ®Google Scholar
• Chen, Y., Chu, B., & Freeman, C. T (2019b). Iterative learning control for robotic path following with trial-varying motion profiles. IEEE/ASME Transactions on Mechatronics. https://doi.org/10.1109/TMECH.2022.3164101
   Google Scholar
• Freeman, C., Rogers, E., Hughes, A. M., Burridge, J., & Meadmore, K (2012). Iterative learning control in health care: Electrical stimulation and robotic-assisted upper-limb stroke rehabilitation. IEEE Control Systems Magazine, 32(1), 18–43. https://doi.org/10.1109/MCS.2011.2173261
   Web of Science ®Google Scholar
• Freeman, C. T., Cai, Z., Rogers, E., & Lewin, P. L (2011). Iterative learning control for multiple point-to-point tracking application. IEEE Transactions on Control Systems Technology, 19(3), 590–600. https://doi.org/10.1109/TCST.2010.2051670
   Web of Science ®Google Scholar
• Fu, M., & Xie, L (2005). The sector bound approach to quantized feedback control. IEEE Transactions on Automatic Control, 50(11), 1698–1711. https://doi.org/10.1109/TAC.2005.858689
   Web of Science ®Google Scholar
• Gao, M., Sheng, L., Zhou, D., & Gao, F (2017). Iterative learning fault-tolerant control for networked batch processes with multirate sampling and quantization effects. Industrial & Engineering Chemistry Research, 56(9), 2515–2525. https://doi.org/10.1021/acs.iecr.6b04609
   Web of Science ®Google Scholar
• Huo, N., & Shen, D (2020). Encoding-decoding mechanism-based finite-level quantized iterative learning control with random data dropouts. IEEE Transactions on Automation Science and Engineering, 17(3), 1343–1360. https://doi.org/10.1109/TASE.2019.2949200
   Web of Science ®Google Scholar
• Jin, X (2018a). Iterative learning control for output-constrained nonlinear systems with input quantization and actuator faults. International Journal of Robust and Nonlinear Control, 28(2), 729–741. https://doi.org/10.1002/rnc.v28.2
   Web of Science ®Google Scholar
• Jin, X (2018b). Fault-tolerant iterative learning control for mobile robots non-repetitive trajectory tracking with output constraints. Automatica, 94, 63–71. https://doi.org/10.1016/j.automatica.2018.04.011
   Web of Science ®Google Scholar
• Johansen, S. V., Jenson, M. R., Chu, B., Bendsten, J. D., Mogensen, J., & Rogers, E (2021). Broiler FCR optimization using norm optimal terminal iterative learning control. IEEE Transactions on Control System Technology, 29(2), 580–592. https://doi.org/10.1109/TCST.87
   Web of Science ®Google Scholar
• Liu, X., Wei, S., & Chai, Y (2020). An iterative learning scheme-based fault estimator design for nonlinear systems with quantised measurements. Journal of the Franklin Institute, 357(1), 606–621. https://doi.org/10.1016/j.jfranklin.2019.09.040
   Web of Science ®Google Scholar
• Meadmre, K. L., Hughes, A. M., Freeman, C. T., Cai, Z., Tong, D., Burridge, J. H., & Rogers, E (2012). Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke. Neurorehabilitation and Neural Repair, 9(32), 559–568. https://doi.org/10.1186/1743-0003-9-32
   Google Scholar
• Oomen, T., & Rojas, C. R (2017). Sparse iterative learning control with application to a wafer stage: Achieving performance, resource efficiency, and task flexibility. Mechatronics, 47, 134–147. https://doi.org/10.1016/j.mechatronics.2017.09.004
   Web of Science ®Google Scholar
• Owens, D. H. (2016). Iterative learning control an optimization paradigm. Springer.
   Google Scholar
• Ratcliffe, J. D. (2004). Iterative learning control implemented on a multi-axis system [Doctoral dissertation]. University of Southampton, UK.
   Google Scholar
• Shen, D., & Xu, Y (2016). Iterative learning control for discrete-time stochastic systems with quantized information. IEEE/CAA Journal of Automatica Sinica, 3(1), 59–67. https://doi.org/10.1109/JAS.2016.7373763
   Google Scholar
• Shen, D., & Zhang, C (2020). Zero-error tracking control under unified quantized iterative learning framework via encoding-decoding method. IEEE Transactions on Cybernetics. https://doi.org/10.1109/TCYB.2020.3004187
   Web of Science ®Google Scholar
• Son, T. D., Ahn, H. S., & Moore, K. L (2013). Iterative learning control in optimal tracking problems with specified data points. Automatica, 49(5), 1465–1472. https://doi.org/10.1016/j.automatica.2013.02.008
   Web of Science ®Google Scholar
• Tao, H., Paszke, W., Rogers, E., Yang, H., & Galkowski, K (2017). Iterative learning fault-tolerant control for differential time-delay batch processes in finite frequency domains. Journal of Process Control, 56, 112–128. https://doi.org/10.1016/j.jprocont.2016.12.007
   Web of Science ®Google Scholar
• Wang, L., Mo, S., Zhou, D., Gao, F., & Chen, X (2012). Robust delay dependent iterative learning fault-tolerant control for batch processes with state delay and actuator failures. Journal of Process Control, 22(7), 1273–1286. https://doi.org/10.1016/j.jprocont.2012.05.016
   Web of Science ®Google Scholar
• Zhang, C., & Shen, D (2018). Zero-error convergence of iterative learning control based on uniform quantization with encoding and decoding mechanism. IET Control Theory & Applications, 12(14), 1907–1915. https://doi.org/10.1049/cth2.v12.14
   Web of Science ®Google Scholar
• Zhou, C., Tao, H., Chen, Y., Stojanovic, V., & Paszke, W (2022). Robust point-to-point iterative learning control for constrained systems: A minimum energy approach. International Journal of Robust and Nonlinear Control. https://doi.org/10.1049/cth2.v12.14
   Google Scholar
• Zhuang, Z., Tao, H., Chen, Y., Stojanovic, V., & Paszke, W (2022). Iterative learning control for repetitive tasks with randomly varying trial lengths using successive projection. International Journal of Adaptive Control and Signal Processing, 36(5), 1196–1215. https://doi.org/10.1002/acs.v36.5
   Web of Science ®Google Scholar