Zero-error convergence of iterative learning control based on uniform quantisation with encoding and decoding mechanism
Zero-error convergence of iterative learning control based on uniform quantisation with encoding and decoding mechanism
- Author(s): Chao Zhang 1 and Dong Shen 1
- DOI: 10.1049/iet-cta.2017.0919
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- Author(s): Chao Zhang 1 and Dong Shen 1
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View affiliations
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Affiliations:
1:
College of Information Science and Technology , Beijing University of Chemical Technology , Beijing 100029 , People's Republic of China
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Affiliations:
1:
College of Information Science and Technology , Beijing University of Chemical Technology , Beijing 100029 , People's Republic of China
- Source:
Volume 12, Issue 14,
24
September
2018,
p.
1907 – 1915
DOI: 10.1049/iet-cta.2017.0919 , Print ISSN 1751-8644, Online ISSN 1751-8652
In this study, the zero-error convergence of the iterative learning control for a tracking problem is realised by incorporating a uniform quantiser with an encoding and decoding mechanism. Under this scheme, the system output is first transformed and encoded. Then, the encoded information is transmitted back for updating the input. The results are extended to a finite quantisation level situation under the same framework and a simulation using a permanent magnet linear motor is performed to demonstrate the effectiveness of the proposed scheme.
Inspec keywords: linear motors; convergence of numerical methods; quantisation (signal); machine control; permanent magnet motors; decoding; iterative learning control
Other keywords: encoding mechanism; iterative learning control; encoded information; uniform quantisation; zero-error convergence; decoding mechanism; permanent magnet linear motor; finite quantisation level situation; tracking problem
Subjects: Interpolation and function approximation (numerical analysis); Codes; Self-adjusting control systems; Linear machines; Interpolation and function approximation (numerical analysis); Control of electric power systems
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