East Wind - Sprint Blog Day2

Miracle_Han 2021-11-15 22:57:13
The Link Your Classhttps://bbs.csdn.net/forums/MUEE308FZ
The Link of Requirement of This Assignmenthttps://bbs.csdn.net/topics/603251839
The Name of TeamEast Wind
The Goal of This AssignmentAlpha Sprint
Leader's MU STU ID and Name19104375 & 831902106 Xiaolong Han
Teammate 1's MU STU ID and Name19104600 & 831902123 Yongquan Wang
Teammate 2's MU STU ID and Name19104847 & 831902119 Jiatong Zhang
Teammate 3's MU STU ID and Name19104821 & 831902118 Shuoyuan Chen
Teammate 4's MU STU ID and Name19104952 & 831901329 Xiaotong Shao
Group number6 - A

📜 Catalog

目录

  • 1. Expected task arrangement and completion status
  • 👨‍🎓Leader: Xiaolong Han__ Miracle
  • 👩‍🎓Teammate 1: Yongquan Wang __ Kerio
  • 👨‍✈️Teammate 2: Jiatong Zhang __ Allen
  • 👨‍⚖️Teammate 3: Shuoyuan Chen __ Dio
  • 👩‍⚖️Teammate 4: Xiaotong Shao __
  • 👨🏿‍🤝‍👨🏿Team member contribution details
  • 2. Project burnout diagram
  • 3. Github check-in logs and screenshots of the project running today show the progress of the development
  • Summary:
  • 4. System UML design diagram and system module class diagram
  • Today's child UML diagram
  • UML design diagrams
  • Class diagram
  • Activity diagram

1. Expected task arrangement and completion status

Everyone's progress today

👨‍🎓Leader: Xiaolong Han__ Miracle
Completed taskTask Completion DurationProblems with completing tasksHandling
Write a daily Blog45mins
👩‍🎓Teammate 1: Yongquan Wang __ Kerio
👨‍✈️Teammate 2: Jiatong Zhang __ Allen
  1. They did the same thing they did yesterday because the back end takes a lot of time to learn
  2. Sorted out the various parts of the knowledge points need to learn, according to the knowledge points download configuration of the relevant procedures and servers
Completed taskTask Completion DurationProblems with completing tasksHandling
Learn about the database SpringBoot and try writing interfacesAll day longThere are so many problems that I don't know how to start. It takes a lot of time to configure the software environment, and it is difficult to implement several teaching videos in practical operation
Learn how to use Java for applets call interfaces

🏫This is the record of our study in Bilibili University

👨‍⚖️Teammate 3: Shuoyuan Chen __ Dio
Completed taskTask Completion DurationProblems with completing tasksHandling
Design homepage 2.060minsDon't know how to code a lot of desired effectsConsult CSDN and many other articles, find the answer from it, and imitate the production principle according to the ink knife prototype.
Vlog record15mins

img

👩‍⚖️Teammate 4: Xiaotong Shao __

Since we have not entered the testing stage, Mr.Shao has not been used at this stage, so we are more asking him to help other teammates

Completed taskTask Completion DurationProblems with completing tasksHandling
Assist in Blog shooting15mins
Assist in Vlog shooting60mins
👨🏿‍🤝‍👨🏿Team member contribution details
MemberContribution DegreeContribution Details
Xiaolong Han20%Blog writing
Yongquan Wang20%Learn about the database SpringBoot and try writing interfaces
Jiatong Zhang20%Learn about the database SpringBoot and try writing interfaces
Shuoyuan Chen21%Set up the Github Library and take vlogs
Xiaotong Shao19%Assist team members in writing Blog and shooting Vlog

2. Project burnout diagram

img

3. Github check-in logs and screenshots of the project running today show the progress of the development

Here is our Github check-in record.

img

Summary:
  • Today is a busy day, but it still seems to be in the same place, the configuration of the server is also continuing to do, the front-end design for a simpler design, so the designer has also changed.
  • The experiment was far more difficult than we thought.

4. System UML design diagram and system module class diagram

Today's child UML diagram

img

UML design diagrams

img

Class diagram

img

Activity diagram

img


#####Sequence diagram

img

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内容概要:本文研究了面向复杂海洋环境的无人水面艇(USV)编队控制问题,提出了一种双层模型预测控制(MPC)理论与鲁棒协同控制方法。上层负责编队构型的优化与全局路径规划,通过求解优化问题实现多艇协同构型的动态调整;下层基于非线性MPC框架实现各无人艇的运动控制与精确轨迹跟踪,充分考虑了系统动力学约束、外部环境干扰(如风浪流)及模型不确定性。通过引入鲁棒控制策略,增强了系统在复杂动态海洋环境下的抗干扰能力与控制稳定性。研究在Matlab平台上完成了算法的完整代码实现与仿真验证,结果表明所提方法能够有效实现多艇在复杂环境下的高精度、强鲁棒性协同编队控制。; 适合人群:具备自动控制、机器人、海洋工程或相关专业背景,熟悉Matlab/Simulink仿真工具,从事多智能体协同控制、无人系统自主导航或模型预测控制算法研究的研发人员与研究生。; 使用场景及目标:①为无人水面艇在复杂、动态、不确定的海洋环境下执行编队任务提供先进的控制理论与技术方案;②通过完整的Matlab代码实现,方便研究人员复现、验证、改进双层MPC与鲁棒协同控制算法;③促进模型预测控制与鲁棒控制理论在多智能体系统、无人装备协同作业等领域的深度融合与应用发展。; 阅读建议:建议读者结合提供的Matlab代码,深入剖析双层控制架构的设计逻辑、MPC优化问题的构建过程以及鲁棒性处理机制的具体实现,重点关注算法如何处理模型误差、外部干扰和系统硬约束,以全面掌握其在复杂场景下的工程应用潜力。

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