MU-SE: Course summary

taohhoat 2023-01-12 22:51:16

MU-SE: Course summary

The Link Your Classhttps://bbs.csdn.net/forums/MUEE308FZU202201
The Link of Requirements of This Assignmenthttps://bbs.csdn.net/topics/611628445
MU STU ID and FZU STU ID20124066&832002123
Video demo linkVideo demo
GitHub linkGithub Link

catelogue

  • MU-SE: Course summary
  • The CSDN links of each Lab
  • Summary and harvest
  • Technology and tools
  • Video link and GitHub link

lablink
Lab1-1 Self Introduction & Course Plan
Lab1-2Keywords extraction and counting
Lab2-1EE308 Lab2-1 Bobing software
Lab2-2EE308 Lab2-2 Final Bobing software
Lab3-1Topic selection and requirement analysis
Lab3-2Group Sprint summary

Summary and harvest

1.personal programming
The first two projects helped me review the usage of the C++, which made me more proficient in C++. First, i met some problems hard to deal with. After long time trying, the problems were solved. Then i tried to optimize the code finally it looks better.
For myself, although I encountered a lot of problems in the process, I always had an optimistic attitude to solve the problems, and finally learned the knowledge perfectly.

2. pair programming
In group programming, we have the clear goals and plans, so we work together really efficiently. In lab2 i worked with my partner Zijun Tang. We together used Axure to design every interfaces and we also programmed the code efficiently. In the process of cooperation, we can understand each other, can promote each other.

在这里插入图片描述



3.On-site programming
On-site programming tests our ability to apply what we know in the field; everyone has to master certain skills to solve problems.

4. team project practice
we worked together to create a website helping people manage the fund. We assigned the tasks and finished the project well within the allotted time.

Technology and tools

Lab1:Markdown editor C++
Lab2:Axure and Android Studio
Lab3: HTML, CSS, and JavaScript

Bobing software video: https://v.youku.com/v_show/id_XNTkxOTc5MTAzMg==.html

Bobing software GitHub link: https://github.com/BlueP0118/EE308_Lab2-2/tree/6b74bb3108fe26b4823c3a39a33d5adc6843ad45

group Team Project video:https://www.bilibili.com/video/BV1Re411c7gM/?vd_source=fe9c12bf738b616a3bca949282c6090d

group Team Project GitHub link:https://github.com/LittleMatcher/EE308FZ-fund

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内容概要:本文围绕“基于超局部模型与自抗扰ESO观测器的无模型预测电流控制改进策略”展开研究,提出一种结合超局部模型(ULM)与扩张状态观测器(ESO)的无模型预测电流控制(MFPCC)改进方法,旨在提升永磁同步电机(PMSM)电流环的动态响应性能与抗干扰能力。该策略利用超局部模型对系统行为进行局部逼近,避免依赖精确数学模型,同时引入自抗扰控制中的ESO实时观测并补偿系统内外部扰动,有效抑制参数摄动、负载变化及模型不确定性带来的影响。研究通过Simulink搭建完整的控制系统仿真模型,对传统MFPCC与所提改进策略进行对比分析,验证了新方法在电流跟踪精度、响应速度和鲁棒性方面的优越性。; 适合人群:具备电机控制、现代控制理论及Simulink仿真基础的电气工程、自动化及相关专业的研究生、科研人员及工程技术人员。; 使用场景及目标:①用于高性能电机驱动系统中电流环控制器的设计与优化;②为无模型控制与自抗扰控制的融合应用提供技术参考;③支撑相关课题的仿真验证、论文复现与创新方法研究。; 阅读建议:建议读者结合Simulink仿真模型深入理解控制结构与参数整定过程,重点关注ESO的观测性能与扰动补偿机制,并可通过改变负载条件、参数偏差等工况进行鲁棒性测试,进一步掌握该改进策略的核心优势与适用边界。

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