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Sparse Command Generator for        Remote Control     Masaaki Nagahara (Kyoto Univ.)Daniel E. Quevedo (The Univ. of Newca...
Remote Control System        Comamnd        Generator                              RobotIn remote control (RC), onehas to ...
Remote Control in Sparse Land        Comamnd        Generator                               RobotFor rate-limited networks...
Table of Contents
Table of Contents
Remote Control Systems                                Target points                Radio Control Helicopter
Remote Control Systems                              Regularization parameter for tradeoff between                         ...
Solution to Energy-limiting control The optimal control is given by                                   [S. Sun et al., IEEE...
Reference vector   Transmitted vector    Control input   Output                             D/A conversion     Plant      ...
Table of Contents
Sparsity-Promoting Optimization
Sparsity-Promoting Optimization
Feasible set
Feasible setSparse!
Feasible setNot sparse
• The solution of  can be effectively obtained via a fast algorithm.                       [Beck-Teboulle, SIAM J. Imag. S...
• The solution of  can be effectively obtained via a fast algorithm.                       [Beck-Teboulle, SIAM J. Imag. S...
Proposed Remote Control Fast Algorithm
A simple way to send a sparse vector
Table of Contents
Examples
Vectors to be sent
Tracking error
Quantizing control vectorsWe quantize the vectors by a uniform quantizer to encode them.
Tracking error with quantization
ConclusionThank you for your attention!
Sparse Command Generator for Remote Control
Sparse Command Generator for Remote Control
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Sparse Command Generator for Remote Control

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M. Nagahara, D. E. Quevedo, J. Ostergaard, T. Matsuda, and K. Hayashi,
Sparse Command Generator for Remote Control,
The 9th IEEE International Conference on Control & Automation (ICCA), pp. 1055-1059, Dec., 2011.

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Transcript of "Sparse Command Generator for Remote Control"

  1. 1. Sparse Command Generator for Remote Control Masaaki Nagahara (Kyoto Univ.)Daniel E. Quevedo (The Univ. of Newcastle) Jan Østergaard (Aalborg Univ.) Takahiro Matsuda (Osaka Univ.) Kazunori Hayashi (Kyoto Univ.)
  2. 2. Remote Control System Comamnd Generator RobotIn remote control (RC), onehas to transmit controlcommands through rate-limited networks such aswireless networks.
  3. 3. Remote Control in Sparse Land Comamnd Generator RobotFor rate-limited networks,control commands should becompressed.Sparse Representation caneffectively compress controlcommands without muchdistortion.
  4. 4. Table of Contents
  5. 5. Table of Contents
  6. 6. Remote Control Systems Target points Radio Control Helicopter
  7. 7. Remote Control Systems Regularization parameter for tradeoff between tracking error and control energyTracking error on the sampling instants Energy limitation
  8. 8. Solution to Energy-limiting control The optimal control is given by [S. Sun et al., IEEE TAC, 2000]
  9. 9. Reference vector Transmitted vector Control input Output D/A conversion Plant Actuator
  10. 10. Table of Contents
  11. 11. Sparsity-Promoting Optimization
  12. 12. Sparsity-Promoting Optimization
  13. 13. Feasible set
  14. 14. Feasible setSparse!
  15. 15. Feasible setNot sparse
  16. 16. • The solution of can be effectively obtained via a fast algorithm. [Beck-Teboulle, SIAM J. Imag. Sci., 2009] [Zibulevsky-Elad, IEEE SP Mag., 2010]
  17. 17. • The solution of can be effectively obtained via a fast algorithm. [Beck-Teboulle, SIAM J. Imag. Sci., 2009] [Zibulevsky-Elad, IEEE SP Mag., 2010]
  18. 18. Proposed Remote Control Fast Algorithm
  19. 19. A simple way to send a sparse vector
  20. 20. Table of Contents
  21. 21. Examples
  22. 22. Vectors to be sent
  23. 23. Tracking error
  24. 24. Quantizing control vectorsWe quantize the vectors by a uniform quantizer to encode them.
  25. 25. Tracking error with quantization
  26. 26. ConclusionThank you for your attention!
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