Fuzzy system-based adaptive iterative learning control for nonlinear plants with initial state errors.
In this paper, a fuzzy system-based adaptive iterative learning controller is proposed for a class of non-Lipschitz nonlinear plants which can repeat a given task over a finite time interval. The variable initial resetting state errors at the beginning of each trial is considered. To overcome the in...
| Veröffentlicht in: | IEEE Transactions on fuzzy systems 12, 5 (2004). |
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| Format: | Artikel |
| Sprache: | English |
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