在机场建设水平迅速提高和建设规模不断扩大的背景下，本书针对大型客机的研发、试飞和运营的需求，采用机器学习、5G数据链和智能图像处理等方法研究了飞机牵引级联系统自动控制仿真。通过机器学习建立了牵引和推动两类模型，并设计了基于5G传输链路的通讯控制协议；在控制过程的研究中，采用机器学习、智能图像处理、数据集构建和5G数据传输等方法，研究了飞机牵引级联系统的稳定性、飞机牵引运动过程的环境识别和运动状态控制；通过仿真实现了飞机牵引的自动控制。
本书可供从事自动控制、模式识别与智能图像处理、5G数据传输等相关专业的研究人员和工程技术人员参考。

刘天畅，男，1992年出生。博士研究生，就读于武汉理工大学。2013年获西南交通大学学士学位，2020年获上海交通大学硕士学位，中国商飞注册系统工程师。主要研究方向为智能装备技术、数据传输与处理技术，以第一作者发表相关研究论文10余篇。目前主要执行大型客机型号任务，开展民用飞机试飞实验等工作。

Chapter One Overview of Aircraft Traction Cascade System
1.1 Introduction
1.2 Transmission and control modes of aircraft tractors
1.2.1 Traction modes
1.2.2 Transmission control system
1.2.3 Hydraulic transmission control system of aircraft towing tra
1.2.4 Automatic control of aircraft tractors
1.3 Aircraft automatic parking and anti-collision system
1.4 Airport FOD intelligent detection
Chapter Two Machine Learning Models and Algorithms
2.1 The development of machine learning
2.1.1 Budding period
2.1.2 Enthusiastic period
2.1.3 Calm period
2.1.4 Revival period
2.1.5 Diversified development period
2.2 Feature engineering
2.2.1 Data structure
2.2.2 Data loading
2.2.3 Data processing
2.2.4 Feature processing
2.2.5 Feature dimensionahty reduction
2.3 Learning methods for dealing with forecasting problems
2.3.1 Linear algebra and machine learning
2.3.2 Univariate linear regression
2.3.3 Multivariate linear regression
2.4 Learning methods for dealing with classification problems
2.4.1 Logistic regression
2.4.2 Classification expression
2.4.3 Logical distribution
2.4.4 Logistic regression solution
2.5 Neural network
2.5.1 Machine learning models
2.5.2 Loss function
2.5.3 Convolutional neural network
2.6 Intelligent image processing methods
Chapter Three Simulation Design of Aircraft Traction Cascade System
3.1 Design of simulation function index
3.2 Simulation parameters design
3.3 Simulation system architecture
3.4 Research methods and technical path
3.4.1 Research methods
3.4.2 Technical path
Chapter Four PID Control and Stability of Aircraft Traction Cascade System
4.1 Motion analysis and control mode of the cascade system
4.1.1 Motion analysis
4.1.2 Steady state control method
4.1.3 PID control
4.2 Tilt angle measurement
4.3 Encoder velocity measurement
4.4 DC motor PID control
4.4.1 Position closed-loop control
4.4.2 Speed closed-loop control
4.5 Cascade system speed control and cascade PID
4.6 PID traction control simulation
4.6.1 Simulation experimental method
4.6.2 Simulation experiments
4.6.3 Simulation experimental results
4.7 Conclusions
Chapter Five Motion Control of Aircraft Traction Cascade System Based on Machine Learning
5.1 Motion control based on machine learning
5.1.1 Motion analysis
5.1.2 Automatic control model
5.2 Environment constrained motion control based on machine learning
5.2.1 Characteristic environmental constraint
5.2.2 The environment constraint of FOD
5.2.3 The environment constraint of runway intrusion
5.3 Results and discussion
5.4 Conclusions
Chapter Six High-Speed Data Transmission for the Aircraft Towing Tractor
6.1 High-Speed communication architecture and environment construction
6.2 High-Speed transmission link design
6.2.1 Transmission link rule design
6.2.2 Sub-packet design
6.3 Results and discussion
6.3.1 Millimeter wave transmission
6.3.2 Full band communication
6.3.3 Response time of control instructions
6.4 Conclusions
Chapter Seven Aircraft Tractor Automatic Control Simulation
7.1 Data collection and annotation
7.1.1 Traction platform configuration information
7.1.2 Training data collection and labeling
7.1.3 Environmental restraint control data collection and labeling
7.2 Model training
7.2.1 Model structure
7.2.2 Model training process
7.3 Model verification
7.3.1 Traction process
7.3.2 Pushing process
7.3.3 Environment constrained motion control
7.3.4 Results of high-speed data link test
7.4 Conclusions
Chapter Eight Summary and Prospect
8.1 Summary
8.2 Prospect
8.2.1 Database construction
8.2.2 Researc