Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Reinforcement Learning Approach for Transient Control of Liquid Rocket
  Engines   Nowadays, liquid rocket engines use closed-loop control at most near steady
operating conditions. The control of the transient phases is traditionally
performed in open-loop due to highly nonlinear system dynamics. This situation
is unsatisfactory, in particular for reusable engines. The open-loop control
system cannot provide optimal engine performance due to external disturbances
or the degeneration of engine components over time. In this paper, we study a
deep reinforcement learning approach for optimal control of a generic
gas-generator engine's continuous start-up phase. It is shown that the learned
policy can reach different steady-state operating points and convincingly adapt
to changing system parameters. A quantitative comparison with carefully tuned
open-loop sequences and PID controllers is included. The deep reinforcement
learning controller achieves the highest performance and requires only minimal
computational effort to calculate the control action, which is a big advantage
over approaches that require online optimization, such as model predictive
control. control.

25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
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The categories of this paper are: funct-an