Volume 13, no. 2Pages 69 - 79

New P-Type and D-Type Iterative Learning Control Update Laws for Networked Control Systems with Random Data Dropouts

S.A. Najafi, A. Delavarkhalafi
In this paper, we present two new P-type and D-type iterative learning control (ILC) update laws for linear stochastic systems with random data dropout modeled with a Bernoulli random variable. We prove that the P-type and D-type ILC update laws converge to the desired input in the almost sure sense. We show that the convergence conditions of the inputs corresponding to the P-type and D-type ILC update laws for networked control systems are the same. We present the performance comparison of the P-type and D-type ILC update laws. In this comparison, we conclude that the P-type ILC update law is more effective than the D-type ILC update law for networked control systems.
Full text
iterative learning control; D-type; P-type; data dropout; networked control linear system.
1. Tayebi A., Abdul S., Zaremba M.B., Ye Y. Robust Iterative Learning Control Design: Application to a Robot Manipulator. Transactions on Mechatronics, 2008, vol. 13, no. 5, pp. 608-613.
2. Arimoto S., Kawamura S., Miyazaki F. Bettering Operation of Robots by Learning. Journal of Intelligent and Robotic Systems, 1984, vol. 1, no. 2, pp. 123-140.
3. Casalino G., Bartolini G. A Learning Procedure for the Control of Movements of Robotic Manipulators. Robotics and Automation, 1984, vol. 2, pp. 108-111.
4. Craig J.J. Adaptive Control of Manipulators Through Repeate Trials. Control Conference, American, 1984, vol. 21, pp. 1566-1573. DOI: 10.1109/ACC.1984.4171549
5. Hyo-Sung Ahn, YangQuan Chen, Moore K.L. Iterative Learning Control: Survey and Categorization. IEEE Transactions on Systems, Man, and Cybernetics, 2007, vol. 37, no. 6, article ID: 10991121, 54 p.
6. Hyo-Sung Ahn, Moore K.L., YangQuan Chen. Iterative Learning Control: Robustness and Monotonic Convergence for Interval System. London, Springer-Verlag, 2007.
7. Hyo-Sung Ahn, Douglas Bristow. Special Issue on Iterative Learning Control. Asian Journal of Control, 2011, vol. 13, no. 1, pp. 1-22.
8. Bien Z., Jian-Xin Xu. Iterative Learning Control Analysis, Design, Integration and Applications. Boston, Kluwer Academic Publishers, 1998.
9. Bristow D.A., Tharayil M., Alleyne A.G. A Survey of Iterative Learning Control: a Learning-Based Method for High-Performance Tracking Control. IEEE Control Systems, 2006, vol. 26, no. 3, pp. 96-114.
10. YangQuan Chen, Changyun Wen. em Iterative Learning Control: Convergence, Robustness and Applications. London, Springer, 1999.
11. Freeman C.T., Youqing Wang. Special Issue on Iterative Learning Control and Repetitive Control. International Journal of Control, 2011, vol. 84, no. 7, pp. 1589-1600.
12. Moore K.L. Iterative Learning Control for Deterministic Systems. London, Springer, 1993.
13. Moore K.L., Jian-Xin Xu. Special Issue on Iterative Learning Control. International Journal of Control, 2000, vol. 73, no. 10, pp. 819-823. DOI: 10.1080/002071700405798
14. Masaru Uchiyama. Formulation of High-Speed Motion Pattern of a Mechanical Arm by Trial. Transactions of the Society of Instrument and Control Engineers, 1978, vol. 14, no. 6, pp. 706-712. DOI: 10.9746/sicetr1965.14.706
15. Shang-Chen Wu, Masayoshi Tomizuka. An Iterative Learning Control Design for Self-Servo Writing in Hard Disk Drives. Mechatronics. 2010, vol. 20, no. 1, pp. 839-844. DOI: 10.3182/20080706-5-KR-1001.00144
16. YangQuan Chen, Moore K.L., Jie Yu, Tao Zhang. Iterative Learning Control and Repetitive Control in Hard Disk Drive Industry. International Journal of Adaptive Control and Signal Processing, 2008, vol. 22, no. 4, pp. 325-343.
17. Freeman C., Lewin P., Rogers E., Ratcliffe J. Iterative Learning Control Applied to a Gantry Robot and Conveyor System. Transactions of the Institute of Measurement and Control, 2010, vol. 32, no. 3, pp. 251-264.
18. Hoelzle D.J., Alleyne A.G., Johnson A.J. Iterative Learning Control for Robotic Deposition Using Machine Vision. American Control Conference, 11-13 June, Washington, USA, 2008, pp. 4541-4547.
19. Inaba K. Iterative Learning Control for Industrial Robots with End Effect or Sensing (PhD dissertation), Berkeley, University of California, 2008.
20. Tao Liu, Furong Gao, Youqing Wang. IMC-Based Iterative Learning Control for Batch Processes with Time Delay Variation. Journal of Process Control, 2010, vol. 20, no. 2, pp. 173-180.
21. Tao Liu, Furong Gao. Robust Two-Dimensional Iterative Learning Control for Batch Processes with State Delay and Time-Varying Uncertainties. Chemical Engineering Science, 2010, vol. 65, no. 23, pp. 6134-6144.
22. Dong Shen, Chao Zhang, Yun Xu. Two Updating Schemes of Iterative Learning Control for Networked Control Systems with Random Data Dropouts. Information Sciences, 2017, vol. 381, pp. 352-370.
23. Youqing Wang, Furong Gao, Doyle F.J. Survey on Iterative Learning Control Repetitive Control and Run-to-Run Control. Journal of Process Control, 2009, vol. 19, no. 10, pp. 1589-1600. DOI: 10.1016/j.jprocont.2009.09.006
24. Dong Shen. Iterative Learning Control with Incomplete Information. Journal of Automatica Sinica, 2018, vol. 5, no. 5, pp. 885-901. DOI: 10.1109/JAS.2018.7511123
25. Saab S. Stochastic P-type/D-Type Iterative Learning Control Algorithms. International Journal of Control, 2003, vol. 76, no. 2, pp. 139-148.
26. Jian Liu, Xiaoe Ruan. Networked Iterative Learning Control for Discrete-Time System with Stochastic Packet Dropouts in Input and Output Channels. Advances in Difference Equations, 2017, vol. 1, pp. 1-21. DOI: 10.1186/s13662-017-1103-8