Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sparsity-Promoting Iterative Learning Control for Resource-Constrained
  Control Systems   We propose novel iterative learning control algorithms to track a reference
trajectory in resource-constrained control systems. In many applications, there
are constraints on the number of control actions, delivered to the actuator
from the controller, due to the limited bandwidth of communication channels or
battery-operated sensors and actuators. We devise iterative learning techniques
that create sparse control sequences with reduced communication and actuation
instances while providing sensible reference tracking precision. Numerical
simulations are provided to demonstrate the effectiveness of the proposed
control method.

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The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
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The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
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The categories of this paper are: solv-int
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
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The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph