Object
Title: Point-to-Point Iterative Learning Control with Quantized Input Signal and Actuator Faults
Creator:
Huang, Yande ; Tao, Hongfeng ; Chen, Yiyang ; Rogers, Eric ; Paszke, Wojciech (1975- )
Date:
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Abstract:
This paper applies iterative learning control to point-to-point tracking problems with a general networked structure. The data is quantized and transmitted through restricted communication channels from the controller to the actuator. Combining a logarithmic quantizer with an encoding and decoding mechanism to quantize the input signals reduces the inuence of the quantization error. ; New design algorithms are developed with conditions for convergence of the tracking error and an extension to fault-tolerant performance under actuator failures. A numerical-based case study demonstrates the application of the new designs, which includes a comparison with another ILC law and the relative merits of the encoding and decoding schemes.
Description:
artykuł zamieszczony w: "International Journal of Control"
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DOI:
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License CC BY 4.0:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
Last modified:
Mar 28, 2024
In our library since:
Mar 28, 2024
Number of object content hits:
6
All available object's versions:
https://www.zbc.uz.zgora.pl/publication/88343
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| Edition name | Date |
|---|---|
| Point-to-Point Iterative Learning Control with Quantized Input Signal and Actuator Faults | Mar 28, 2024 |
