Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Preliminary Study on A Physical Model Oriented Learning Algorithm with
  Application to UAVs   This paper provides a preliminary study for an efficient learning algorithm
by reasoning the error from first principle physics to generate learning
signals in near real time. Motivated by iterative learning control (ILC), this
learning algorithm is applied to the feedforward control loop of the unmanned
aerial vehicles (UAVs), enabling the learning from errors made by other UAVs
with different dynamics or flying in different scenarios. This learning
framework improves the data utilization efficiency and learning reliability via
analytically incorporating the physical model mapping, and enhances the
flexibility of the model-based methodology with equipping it with the
self-learning capability. Numerical studies are performed to validate the
proposed learning algorithm.

22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th