Monotonically convergent iterative learning control for linear discrete-time systems
نویسندگان
چکیده
In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking error norms are derived. By using the Markov parameters, it is shown in the time-domain that there exists a non-increasing function such that when the properly chosen constant learning gain is multiplied by this function, the convergence of the tracking error norms is monotonic, without resort to high-gain feedback. 2005 Elsevier Ltd. All rights reserved.
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ورودعنوان ژورنال:
- Automatica
دوره 41 شماره
صفحات -
تاریخ انتشار 2005