Robustness and convergence rate of a discrete‐time learning control algorithm for a class of nonlinear systems
In this paper, we apply a discrete‐time learning algorithm to a class of discrete‐time varying nonlinear systems with affine input action and linear output having relative degree one. We investigate the robustness of the algorithm to state disturbance, measurement noise and reinitialization errors....
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1999
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| Online Access: | http://hdl.handle.net/10725/11176 https://doi.org/10.1002/(SICI)1099-1239(19990730)9:9<559::AID-RNC421>3.0.CO;2-J http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291099-1239%2819990730%299%3A9%3C559%3A%3AAID-RNC421%3E3.0.CO%3B2-J |
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http://hdl.handle.net/10725/11176https://doi.org/10.1002/(SICI)1099-1239(19990730)9:9<559::AID-RNC421>3.0.CO;2-J
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291099-1239%2819990730%299%3A9%3C559%3A%3AAID-RNC421%3E3.0.CO%3B2-J