Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Enhanced MPPT Method based on ANN-assisted Sequential Monte Carlo and
  Quickest Change Detection   The performance of a photovoltaic system is subject to varying environmental
conditions, and it becomes more challenging to track the maximum power point
(MPP) and maintain the optimal performance when partial shading occurs. In this
paper, we propose an enhanced maximum power point tracking (MPPT) method
utilizing the state estimation by the sequential Monte Carlo (SMC) filtering
which is assisted by the prediction of MPP via an artificial neural network
(ANN). A state-space model for the sequential estimation of MPP is proposed in
the framework of incremental conductance (I-C) MPPT approach, and the ANN model
based on the observed voltage and current or irradiance data predicts the
global MPP (GMPP) to refine the estimation by SMC. Moreover, a quick
irrandiance change detection method is applied, such that the SMC-based MPPT
method resorts to the assistance from ANN only when partial shading is
detected. Simulation results show that the proposed enhanced MPPT method
achieves high efficiency and is robust to rapid irradiance change under
different noise levels.

21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph