IEEE/CAA Journal of Automatica Sinica
Citation: | Z. Zhang, H. Jiang, D. Shen, and S. Saab, “Data-driven learning control algorithms for unachievable tracking problems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 1, pp. 205–218, Jan. 2024. doi: 10.1109/JAS.2023.123756 |
[1] |
D. A. Bristow, M. Tharayil, and A. G. Alleyne, “A survey of iterative learning control,” IEEE Control Systems, vol. 26, no. 3, pp. 96–114, 2006. doi: 10.1109/MCS.2006.1636313
|
[2] |
S. R. Nekoo, J. Á. Acosta, G. Heredia, and A. Ollero, “A PD-type state-dependent riccati equation with iterative learning augmentation for mechanical systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 8, pp. 1499–1511, 2022. doi: 10.1109/JAS.2022.105533
|
[3] |
D. Shen and C. Zhang, “Zero-error tracking control under unified quantized iterative learning framework via encodingdecoding method,” IEEE Trans. Cybernetics, vol. 52, no. 4, pp. 1979–1991, 2022. doi: 10.1109/TCYB.2020.3004187
|
[4] |
D. Shen, N. Huo, and S. S. Saab, “A probabilistically quantized learning control framework for networked linear systems,” IEEE Trans. Neural Networks and Learning Systems, vol. 33, no. 12, pp. 7559–7573, 2022. doi: 10.1109/TNNLS.2021.3085559
|
[5] |
D. Shen and Y. Xu, “Iterative learning control for discrete-time stochastic systems with quantized information,” IEEE/CAA J. Autom. Sinica, vol. 3, no. 1, pp. 59–67, 2016. doi: 10.1109/JAS.2016.7373763
|
[6] |
S. S. Saab, “Stochastic P-type/D-type iterative learning control algorithms,” Int. Journal of Control, vol. 76, no. 2, pp. 139–148, 2003. doi: 10.1080/0020717031000077717
|
[7] |
X. Dai, S. Tian, Y. Peng, and W. Luo, “Closed-loop P-type iterative learning control of uncertain linear distributed parameter systems,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 3, pp. 267–273, 2014. doi: 10.1109/JAS.2014.7004684
|
[8] |
D. Meng and K. L. Moore, “Robust iterative learning control for nonrepetitive uncertain systems,” IEEE Trans. Automatic Control, vol. 62, no. 2, pp. 907–913, 2017. doi: 10.1109/TAC.2016.2560961
|
[9] |
C. Liu and X. Ruan, “Input-output-driven gain-adaptive iterative learning control for linear discrete-time-invariant systems,” Int. J. Robust and Nonlinear Control, vol. 31, no. 17, pp. 8551–8568, 2021. doi: 10.1002/rnc.5753
|
[10] |
R. Chi, H. Zhang, B. Huang, and Z. Hou, “Quantitative data-driven adaptive iterative learning control: From trajectory tracking to point-to-point tracking,” IEEE Trans. Cybernetics, vol. 52, no. 6, pp. 4859–4873, 2022. doi: 10.1109/TCYB.2020.3015233
|
[11] |
S. He, W. Chen, D. Li, Y. Xi, Y. Xu, and P. Zheng, “Iterative learning control with data-driven-based compensation,” IEEE Trans. Cybernetics, vol. 52, no. 8, pp. 7492–7503, 2022. doi: 10.1109/TCYB.2020.3041705
|
[12] |
C. Hu, R. Zhou, Z. Wang, Y. Zhu, and M. Tomizuka, “Real-time iterative compensation framework for precision mechatronic motion control systems,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 7, pp. 1218–1232, 2022. doi: 10.1109/JAS.2022.105689
|
[13] |
X. Bu, Z. Hou, S. Jin, and R. Chi, “An iterative learning control design approach for networked control systems with data dropouts,” Int. J. Robust and Nonlinear Control, vol. 26, no. 1, pp. 91–109, 2016. doi: 10.1002/rnc.3300
|
[14] |
J. Chen, C. Hua, and X. Guan, “Iterative learning model-free control for networked systems with dual-direction data dropouts and actuator faults,” IEEE Trans. Neural Networks and Learning Systems, vol. 32, no. 11, pp. 5232–5240, 2021. doi: 10.1109/TNNLS.2020.3027651
|
[15] |
H.-S. Ahn, K. L. Moore, and Y. Chen, “Stability of discrete-time iterative learning control with random data dropouts and delayed controlled signals in networked control systems,” in Proc. 10th Int. Conf. Control, Automation, Robotics and Vision, 2008, pp. 757–762.
|
[16] |
J. Liu and X. Ruan, “Networked iterative learning control design for discrete-time systems with stochastic communication delay in input and output channels,” Int. J. Systems Science, vol. 48, no. 9, pp. 1844–1855, 2017. doi: 10.1080/00207721.2017.1289567
|
[17] |
X. Li, J.-X. Xu, and D. Huang, “An iterative learning control approach for linear systems with randomly varying trial lengths,” IEEE Trans. Automatic Control, vol. 59, no. 7, pp. 1954–1960, 2014. doi: 10.1109/TAC.2013.2294827
|
[18] |
D. Shen and S. S. Saab, “Noisy-output-based direct learning tracking control with Markov nonuniform trial lengths using adaptive gains,” IEEE Trans. Automatic Control, vol. 67, no. 8, pp. 4123–4130, 2022. doi: 10.1109/TAC.2021.3106860
|
[19] |
X. Li, K. Wang, and D. Liu, “An improved result of multiple model iterative learning control,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 3, pp. 315–322, 2014. doi: 10.1109/JAS.2014.7004689
|
[20] |
D. Shen, G. Qu, and X. Yu, “Averaging techniques for balancing learning and tracking abilities over fading channels,” IEEE Trans. Automatic Control, vol. 66, no. 6, pp. 2636–2651, 2021. doi: 10.1109/TAC.2020.3011329
|
[21] |
S. Zhu, X. Wang, and H. Liu, “Observer-based iterative and repetitive learning control for a class of nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 990–998, 2018. doi: 10.1109/JAS.2017.7510463
|
[22] |
G. Qu and D. Shen, “Stochastic iterative learning control with faded signals,” IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1196–1208, 2019. doi: 10.1109/JAS.2019.1911696
|
[23] |
D. Shen and X. Yu, “Learning tracking over unknown fading channels based on iterative estimation,” IEEE Trans. Neural Networks and Learning Systems, vol. 33, no. 1, pp. 48–60, 2022. doi: 10.1109/TNNLS.2020.3027475
|
[24] |
Y. Chen, C. Wen, Z. Gong, and M. Sun, “An iterative learning controller with initial state learning,” IEEE Trans. Automatic Control, vol. 44, no. 2, pp. 371–376, 1999. doi: 10.1109/9.746269
|
[25] |
Y. Hui, R. Chi, B. Huang, and Z. Hou, “Extended state observer-based data-driven iterative learning control for permanent magnet linear motor with initial shifts and disturbances,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 51, no. 3, pp. 1881–1891, 2021. doi: 10.1109/TSMC.2019.2907379
|
[26] |
X. He, Z. Sun, Z. Geng, and A. Robertsson, “Exponential set-point stabilization of underactuated vehicles moving in three-dimensional space,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 2, pp. 270–282, 2022. doi: 10.1109/JAS.2021.1004323
|
[27] |
D. Shen, C. Liu, L. Wang, and X. Yu, “Iterative learning tracking for multisensor systems: A weighted optimization approach,” IEEE Trans. Cybernetics, vol. 51, no. 3, pp. 1286–1299, 2021. doi: 10.1109/TCYB.2019.2942105
|
[28] |
Z. Zhang, H. Jiang, and D. Shen, “Extended iterative learning control for inconsistent tracking problems with random dropouts,” in Proc. IEEE 11th Data Driven Control and Learning Systems Conf., 2022, pp. 935–940.
|
[29] |
R. Chi, Z. Hou, B. Huang, and S. Jin, “A unified data-driven design framework of optimality-based generalized iterative learning control,” Computers &Chemical Engineering, vol. 77, pp. 10–23, 2015.
|
[30] |
L. Ma, X. Liu, X. Kong, and K. Y. Lee, “Iterative learning model predictive control based on iterative data-driven modeling,” IEEE Trans. Neural Networks and Learning Systems, vol. 32, no. 8, pp. 3377–3390, 2021. doi: 10.1109/TNNLS.2020.3016295
|
[31] |
S. S. Saab, D. Shen, M. Orabi, D. Kors, and R. H. Jaafar, “Iterative learning control: Practical implementation and automation,” IEEE Trans. Industrial Electronics, vol. 69, no. 2, pp. 1858–1866, 2022. doi: 10.1109/TIE.2021.3063866
|
[32] |
R. A. Horn and C. R. Johnson, Matrix Analysis. Cambridge University Press, 1985.
|
[33] |
D. Shen, “Iterative learning control with incomplete information: A survey,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 885–901, 2018. doi: 10.1109/JAS.2018.7511123
|
[34] |
H.-S. Ahn, K. Moore, and Y. Chen, “Monotonic convergent iterative learning controller design based on interval model conversion,” IEEE Trans. Automatic Control, vol. 51, no. 2, pp. 366–371, 2006. doi: 10.1109/TAC.2005.863498
|
[35] |
H.-S. Ahn, K. L. Moore, and Y. Chen, “Stability analysis of discrete-time iterative learning control systems with interval uncertainty,” Automatica, vol. 43, no. 5, pp. 892–902, 2007. doi: 10.1016/j.automatica.2006.11.020
|
[36] |
J. H. Lee, K. S. Lee, and W. C. Kim, “Model-based iterative learning control with a quadratic criterion for time-varying linear systems,” Automatica, vol. 36, no. 5, pp. 641–657, 2000. doi: 10.1016/S0005-1098(99)00194-6
|