- Title
- Sparse representations for packetized predictive networked control
- Creator
- Nagahara, Masaaki; Quevedo, Daniel E.
- Relation
- 18th International Federation of Automatic Control (IFAC) World Congress. Proceedings of the 18th World Congress: The International Federation of Automatic Control (Milano, Italy 28 August - 2 September, 2011) p. 84-89
- Publisher Link
- http://dx.doi.org/10.3182/20110828-6-IT-1002.01715
- Publisher
- International Federation of Automatic Control (IFAC)
- Resource Type
- conference paper
- Date
- 2011
- Description
- We investigate a networked control architecture for LTI plant models with a scalar input. Communication from controller to actuator is over an unreliable network which introduces packet dropouts. To achieve robustness against dropouts, we adopt a packetized predictive control paradigm wherein each control packet transmitted contains tentative future plant input values. The novelty of our approach is that we seek that the control packets transmitted be sparse. For that purpose, we adapt tools from the area of compressed sensing and propose to design the control packets via on-line minimization of a suitable ℓ¹/ℓ² cost function. We then show how to choose parameters of the cost function to ensure that the resultant closed loop system be practically stable, provided the maximum number of consecutive packet dropouts is bounded. A numerical example illustrates that sparsity reduces bit-rates, thereby making our proposal suited to control over unreliable and bit-rate limited networks.
- Subject
- networked control; model predictive control; sparse representation; ℓ¹/ℓ² optimization
- Identifier
- http://hdl.handle.net/1959.13/920835
- Identifier
- uon:9215
- Identifier
- ISBN:9783902661937
- Identifier
- ISSN:1474-6670
- Language
- eng
- Full Text
- Reviewed
- Hits: 1694
- Visitors: 2449
- Downloads: 428
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT02 | Author final version | 100 KB | Adobe Acrobat PDF | View Details Download |