Improving Boundary Level Calculation in Quantized Iterative Learning Control With Encoding and Decoding Mechanism
This paper investigates an iterative learning control for single-input, single-output, and linear time-invariant discrete system. The special design of the learning gain matrix is introduced, where a finite uniform quantizer is incorporated with an encoding and decoding mechanism to realize the zero...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8719965/ |
| Summary: | This paper investigates an iterative learning control for single-input, single-output, and linear time-invariant discrete system. The special design of the learning gain matrix is introduced, where a finite uniform quantizer is incorporated with an encoding and decoding mechanism to realize the zero-error convergence of a tracking problem. Furthermore, the boundary-level calculation is considerably improved using lifting technique and infinity-norm of vectors under this mechanism. Some illustrations of the simulations verify the theoretical results. |
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| ISSN: | 2169-3536 |