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% 采用ieee会议类型
\documentclass[conference]{IEEEtran}
%\usepackage{ctex}%引入中文包 摘要、引用等变成中文

\usepackage{graphicx}%插入图片

\begin{document}
	
%************************************标题************************************
\title{Practice Demo for IEEE Conferences}

\author{\IEEEauthorblockN{Luodong Xu}
\IEEEauthorblockA{Northeastern University\\
Shenyang,China \\
Email: 1970762@stu.edu.neu.cn}}
\maketitle 

%************************************摘要************************************
\begin{abstract}
The abstract goes here\cite{refer1}.hello world\cite{refer2} !An example\cite{refer3} of a floating figure using the graphicx package.Note that must occur AFTER (or within).For figures,  should occur after the .Note that IEEEtran v1.7 and later has special internal code that is designed to preserve the operation of within  even when the captionsoff option is in effect. However, because of issues like this, it may be the safest practice to put al

\end{abstract}


%************************************一级************************************
\section{Introduction}
	%用$...$   $$...$$包围的内容表示数学模式
Let $f(x)$ be defined by the formula\cite{refer2}
$$f(x)=3x^2+x-1$$which is a polynomial of degree 2.Traditional learning approaches proposed for controlling quadrotors or helicopters have focused on improving performance for specific trajectories by iteratively improving upon a nominal controller, for example learning from demonstrations, iterative learning, and reinforcement learning. In these schemes, however, it is not clear how the information gathered from the training trajectorie


%************************************二级************************************
\subsection{Subsection Heading Here}
Traditional learning approaches proposed for controlling quadrotors or helicopters have focused on improving performance for specific trajectories by iteratively improving upon a nominal controller, 
for example learning, Fig\ref{fig1} shows how it works.

%************************************插图************************************
\begin{figure}[ht]
\centering
\includegraphics[width=3.5in]{fig.png}
\caption{success}
\label{fig1}
\end{figure}

\begin{figure}[ht]
	\centering
	\includegraphics[width=3.5in]{fig2.pdf}
	\caption{success}
	\label{fig2}
\end{figure}
%************************************三级************************************
\subsubsection{Subsubsection Heading Here}
Traditional learning approaches proposed for controlling quadrotors or helicopters have focused on improving performance for specific trajectories by iteratively improving upon a nominal controller, for example learning from demonstrations, iterative learning, and reinforcement learning. In these schemes, however, it is not clear how the information gathered from the training trajectorie


\section{Conclusion}
The conclusion goes here.


%************************************参考文献************************************
%mybibtexrefer：ieee或者其cite类型为BibTex的论文属性添加到mybibtexrefer.bib即可
\bibliographystyle{IEEEtran}%ieee显示格式
	
	\bibliography{mybibtexrefer}%自己的库
	
\end{document}

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@INPROCEEDINGS{refer1,
author={A. {Punjani} and P. {Abbeel}},
booktitle={2015 IEEE International Conference on Robotics and Automation (ICRA)},
title={Deep learning helicopter dynamics models},
year={2015},
volume={},
number={},
pages={3223-3230},
keywords={aircraft control;helicopters;mechanical engineering computing;neural nets;regression analysis;vehicle dynamics;deep learning helicopter dynamics models;system identification;direct high-dimensional regression;rectified linear unit network model;ReLU network model;hierarchical neural network model;aerobatic maneuvers;Helicopters;Mathematical model;Trajectory;Aerodynamics;Acceleration;Data models;Training},
doi={10.1109/ICRA.2015.7139643},
ISSN={1050-4729},
month={May},}

@inproceedings{refer2,
author = {Nascimento, Renato and Fricke, Kajetan and Viana, Felipe},
year = {2020},
month = {01},
pages = {},
title = {Quadcopter Control Optimization through Machine Learning},
doi = {10.2514/6.2020-1148}
}

@article{refer3,
	title={Learning quadrotor dynamics using neural network for flight control},
	author={Somil Bansal and Anayo K. Akametalu and Frank Jiang and Forrest Laine and Claire J. Tomlin},
	journal={2016 IEEE 55th Conference on Decision and Control (CDC)},
	year={2016},
	pages={4653-4660}
}