http://iet.metastore.ingenta.com
1887

Zero-error convergence of iterative learning control based on uniform quantisation with encoding and decoding mechanism

Zero-error convergence of iterative learning control based on uniform quantisation with encoding and decoding mechanism

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this study, the zero-error convergence of the iterative learning control for a tracking problem is realised by incorporating a uniform quantiser with an encoding and decoding mechanism. Under this scheme, the system output is first transformed and encoded. Then, the encoded information is transmitted back for updating the input. The results are extended to a finite quantisation level situation under the same framework and a simulation using a permanent magnet linear motor is performed to demonstrate the effectiveness of the proposed scheme.

References

    1. 1)
      • 1. Ahn, H., Chen, Y., Moore, K.L.: ‘Iterative learning control: brief survey and categorization’, IEEE Trans. Syst. Man Cybern. C, 2007, 37, (6), pp. 10991121.
    2. 2)
      • 2. Shen, D., Wang, Y.: ‘Survey on stochastic iterative learning control’, J. Process Control, 2014, 24, (12), pp. 6477.
    3. 3)
      • 3. Arimoto, S., Kawamura, S., Miyazaki, F.: ‘Bettering operation of robots by learning’, J. Robot. Syst., 1984, 1, (2), pp. 123140.
    4. 4)
      • 4. Bu, X., Wang, T., Hou, Z., et al: ‘Iterative learning control for discrete-time systems with quantised measurements’, IET Control Theory Applic., 2015, 9, (9), pp. 14551460.
    5. 5)
      • 5. Xu, Y., Shen, D., Bu, X.: ‘Zero-error convergence of iterative learning control using quantized error information’, IMA J. Math. Control Inf., 2017, 34, (1), pp. 10611077.
    6. 6)
      • 6. Shen, D., Xu, Y.: ‘Iterative learning control for discrete-time stochastic systems with quantized information’, IEEE/CAA J. Autom. Sin., 2016, 3, (1), pp. 5967.
    7. 7)
      • 7. Bu, X., Hou, Z., Cui, L., et al: ‘Stability analysis of quantized iterative learning control systems using lifting representation’, Int. J. Adapt. Control and Signal Process., 2017, 31, (9), pp. 13271336.
    8. 8)
      • 8. Zhang, T., Li, J.: ‘Event-triggered iterative learning control for multi-agent systems with quantization’, Asian J. Control, online, DOI: 10.1002/asjc.1450.
    9. 9)
      • 9. Xiong, W., Yu, X., Patel, R., et al: ‘Iterative learning control for discrete-time systems with event-triggered transmission strategy and quantization’, Automatica, 2016, 72, pp. 8491.
    10. 10)
      • 10. Zhang, T., Li, J.: ‘Iterative learning control for multi-agent systems with finite-leveled sigma-delta quantization and random packet losses’, IEEE Trans. Circuits and Syst. I, Regul. Pap., 2017, 64, (8), pp. 21712181.
    11. 11)
      • 11. Li, T., Xie, L.: ‘Distributed consensus over digital networks with limited bandwidth and time-varying topologies’, Automatica, 2011, 47, (9), pp. 20062015.
    12. 12)
      • 12. Li, T., Xie, L.: ‘Distributed coordination of multi-agent systems with quantized-observer based encoding-decoding’, IEEE Trans. Autom. Control, 2012, 57, (12), pp. 30233037.
    13. 13)
      • 13. Zhang, C., Shen, D.: ‘Zero-error convergence of iterative learning control using uniform quantizer with encoding and decoding method’. The 36th Chinese Control Conf. (CCC2017), Dalian, China, 26–28 July 2017, pp. 34733478.
    14. 14)
      • 14. Zhou, W., Yu, M., Huang, D.: ‘A high-order internal model based iterative learning control scheme for discrete linear time-varying systems’, Int. J. Autom. Comput., 2015, 12, (3), pp. 330336.
    15. 15)
      • 15. Xu, J.: ‘Iterative learning control for output-constrained nonlinear systems with input quantization and actuator faults’, Int. J. Robust and Nonlinear Control, 2018, 28, (2), pp. 729741.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2017.0919
Loading

Related content

content/journals/10.1049/iet-cta.2017.0919
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address