Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Recurrent Neural Network Controllers Synthesis with Stability Guarantees
  for Partially Observed Systems   Neural network controllers have become popular in control tasks thanks to
their flexibility and expressivity. Stability is a crucial property for
safety-critical dynamical systems, while stabilization of partially observed
systems, in many cases, requires controllers to retain and process long-term
memories of the past. We consider the important class of recurrent neural
networks (RNN) as dynamic controllers for nonlinear uncertain
partially-observed systems, and derive convex stability conditions based on
integral quadratic constraints, S-lemma and sequential convexification. To
ensure stability during the learning and control process, we propose a
projected policy gradient method that iteratively enforces the stability
conditions in the reparametrized space taking advantage of mild additional
information on system dynamics. Numerical experiments show that our method
learns stabilizing controllers while using fewer samples and achieving higher
final performance compared with policy gradient.

31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat