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Robust Quantized ILC design for Linear Systems Using a 2-D Model
- Source :
- 2016 Chinese Control and Decision Conference (CCDC).
- Publication Year :
- 2016
- Publisher :
- IEEE, 2016.
-
Abstract
- This paper considers the problem of iterative learning control design for linear systems with data quantization, where the system matrices contain uncertain parameters. It is assumed that the control input update signals are quantized before they are transmitted to the iterative learning controller. A logarithmic quantizer is used to decode the signal with a number of quantization levels. Then, a 2-D Roesser model is established to describe the entire dynamics of the ILC system. By using sector bound method, a sufficient asymptotically stability condition for such 2-D system is established and then the ILC design can be given simultaneously. The effectiveness of the proposed method is illustrated by a numerical example.
- Subjects :
- 0209 industrial biotechnology
020208 electrical & electronic engineering
Iterative learning control
Linear system
02 engineering and technology
Data modeling
Quantization (physics)
020901 industrial engineering & automation
Exponential stability
2 d model
Robustness (computer science)
Control theory
Control system
0202 electrical engineering, electronic engineering, information engineering
Mathematics
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2016 Chinese Control and Decision Conference (CCDC)
- Accession number :
- edsair.doi...........f9f724dc59eceef72fce7149d7a1926d