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无人机编队控制模型

本仓库包含了基于环形拓扑的无人机编队控制算法实现，分为2D平面编队和3D空间编队两种模式。

项目结构

本项目包含原始版本和更新版本的编队控制算法实现：

• 原始版本：ring_formation_control_main_2D.m和ring_formation_control_3D.m
• 更新版本：ring_formation_control_main_2D_update.m和ring_formation_control_3D_update.m

版本区别

• 2D编队控制：

  • 原始版本：基础的环形拓扑2D编队控制实现
  • 更新版本：优化了控制参数，提高了编队稳定性和收敛速度，增强了对外部干扰的抵抗能力

• 3D编队控制：

  • 原始版本：基础的3D空间编队控制实现
  • 更新版本：改进了高度协同算法，增强了碰撞避免功能，优化了姿态控制精度

2D平面编队控制

方法介绍

2D平面编队控制基于环形拓扑结构，通过分布式控制算法实现多无人机在平面内的编队飞行。主要特点：

1. 环形拓扑结构：每个无人机只与相邻的两个无人机通信，形成环形通信网络
2. 分布式控制：无需中央控制器，每个无人机基于局部信息做出决策
3. 一致性算法：通过一致性理论保证所有无人机最终达到期望的编队形状
4. 自适应控制：能够适应外部干扰和初始位置的不确定性

演示效果

3D空间编队控制

方法介绍

3D空间编队控制在2D编队的基础上，扩展到三维空间，实现更复杂的立体编队飞行。主要特点：

1. 三维空间控制：实现无人机在三维空间的编队控制
2. 高度协同：在保持平面编队的同时，协调控制高度变化
3. 姿态控制：考虑无人机的姿态动力学，实现更精确的空间编队
4. 鲁棒性设计：对外部扰动和参数不确定性具有较强的鲁棒性
5. 碰撞避免：包含碰撞避免算法，确保编队过程中无人机之间不发生碰撞

演示效果

算法实现

本项目中的编队控制算法主要基于以下理论：

• 图论和拓扑控制
• 一致性理论
• 非线性控制
• 分布式优化

算法在MATLAB环境中实现，通过仿真验证了算法的有效性和稳定性。

使用说明

1. 运行2D编队控制：
   • 基础版本：执行ring_formation_control_main_2D.m
   • 优化版本：执行ring_formation_control_main_2D_update.m（推荐）
2. 运行3D编队控制：
   • 基础版本：执行ring_formation_control_3D.m
   • 优化版本：执行ring_formation_control_3D_update.m（推荐）
3. 仿真结果将保存在对应的frames文件夹中

图像处理工具

仓库中包含了用于处理仿真生成图像的Python脚本：

• uav_ring_formation2D_update/frames_1/合并.py：用于处理和合并2D编队仿真图像
• uav_ring_formation3D_update/frames_2/新建文本文档.py：用于处理和合并3D编队仿真图像 这些工具可以帮助生成编队过程的可视化展示。

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🇨🇳 中文文档 | 🇺🇸 English

UAV Formation Control Model

This repository contains implementations of UAV formation control algorithms based on ring topology, divided into 2D planar formation and 3D spatial formation modes.

Project Structure

This project includes both original and updated versions of formation control algorithm implementations:

• Original versions: ring_formation_control_main_2D.m and ring_formation_control_3D.m
• Updated versions: ring_formation_control_main_2D_update.m and ring_formation_control_3D_update.m

Version Differences

• 2D Formation Control:

  • Original version: Basic implementation of ring topology 2D formation control
  • Updated version: Optimized control parameters, improved formation stability and convergence speed, enhanced resistance to external disturbances

• 3D Formation Control:

  • Original version: Basic implementation of 3D spatial formation control
  • Updated version: Improved height coordination algorithm, enhanced collision avoidance functionality, optimized attitude control precision

2D Planar Formation Control

Method Introduction

2D planar formation control is based on ring topology structure, implementing multi-UAV formation flight in a plane through distributed control algorithms. Main features:

1. Ring Topology Structure: Each UAV only communicates with two adjacent UAVs, forming a ring communication network
2. Distributed Control: No central controller needed, each UAV makes decisions based on local information
3. Consensus Algorithm: Ensures all UAVs eventually achieve the desired formation shape through consensus theory
4. Adaptive Control: Able to adapt to external disturbances and initial position uncertainties

Demonstration Effect

3D Spatial Formation Control

Method Introduction

3D spatial formation control extends 2D formation to three-dimensional space, implementing more complex spatial formation flight. Main features:

1. Three-dimensional Space Control: Implements UAV formation control in three-dimensional space
2. Height Coordination: Coordinates height changes while maintaining planar formation
3. Attitude Control: Considers UAV attitude dynamics for more precise spatial formation
4. Robust Design: Strong robustness to external disturbances and parameter uncertainties
5. Collision Avoidance: Includes collision avoidance algorithms to ensure no collisions between UAVs during formation

Demonstration Effect

Algorithm Implementation

The formation control algorithms in this project are mainly based on the following theories:

• Graph theory and topology control
• Consensus theory
• Nonlinear control
• Distributed optimization

The algorithms are implemented in MATLAB environment, and their effectiveness and stability have been verified through simulation.

Usage Instructions

1. Run 2D formation control:
   • Basic version: Execute ring_formation_control_main_2D.m
   • Optimized version: Execute ring_formation_control_main_2D_update.m (recommended)
2. Run 3D formation control:
   • Basic version: Execute ring_formation_control_3D.m
   • Optimized version: Execute ring_formation_control_3D_update.m (recommended)
3. Simulation results will be saved in the corresponding frames folder

Image Processing Tools

The repository contains Python scripts for processing simulation-generated images:

• uav_ring_formation2D_update/frames_1/合并.py: For processing and merging 2D formation simulation images
• uav_ring_formation3D_update/frames_2/新建文本文档.py: For processing and merging 3D formation simulation images

These tools help generate visual presentations of the formation process.