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Drone Fuzzy Control System Documentation

This document provides a detailed explanation of the components, methods, and logic implemented in the Drone Fuzzy Control System.

Table of Contents

Overview

This project implements a fuzzy logic control system for managing the altitude of a drone. It uses fuzzy models, MQTT communication, and a Streamlit interface to allow real-time data visualization and interaction.

Project Structure


src/
├── data/
│   └── posicao_atual.txt          # Stores current drone position
├── fuzzy/
│   ├── models/
│   │   └── fuzzy_models.py        # Fuzzy models for control system
│   ├── utils/
│   │   └── fuzzy_utils.py         # Utility functions for fuzzy logic
│   └── fuzzy_control.py           # Implements the FuzzyControl class
├── interface/
│   └── streamlit_app.py           # Streamlit app for UI
├── mqtt/
│   └── mqtt_client.py             # MQTT client for communication
└── main.py                        # Main entry point for running the app

Code Descriptions

FuzzyModels Class

File: fuzzy/models/fuzzy_models.py

The FuzzyModels class defines fuzzy logic models and membership functions.

Key Methods:

  • __init__(): Initializes fuzzy variables Erro, dErro, and PotenciaMotor.
  • pertinence(): Defines membership functions for input and output variables.
  • pertinence_error_plot(): Visualizes membership functions for Erro.
  • pertinence_derror_plot(): Visualizes membership functions for dErro.
  • pertinence_potencia_motor_plot(): Visualizes membership functions for PotenciaMotor.
  • pertinence_plots(): Displays all pertinence plots.
  • rules(): Defines a set of fuzzy control rules.

Usage:

This class is used to create fuzzy models and define control rules for the drone's altitude management.

FuzzyControl Class

File: fuzzy/fuzzy_control.py

The FuzzyControl class applies fuzzy logic to compute altitude changes based on the current state of the drone.

Key Methods:

  • __init__(): Initializes the control system using FuzzyModels.
  • infer_rules(): Generates a DataFrame of fuzzy rules for visualization.
  • Subir_e_Descer(Pos_Final): Calculates the drone's position using fuzzy logic.
  • set_home(): Sets the current position as the "home" position.
  • go_to_home(): Moves the drone to the home position.
  • ligar(altura): Takes off the drone to a specified altitude.

Usage:

This class is responsible for handling the drone's movement logic, computing errors, and managing control rules.

StreamlitApp Class

File: interface/streamlit_app.py

The StreamlitApp class provides a user interface for interacting with the drone control system.

Key Methods:

  • __init__(mqtt_client, fuzzy_control): Initializes the app with an MQTT client and fuzzy control object.
  • run(): Runs the Streamlit app with tabs for sending and visualizing data.
  • send_data_tab(): Allows users to input altitude and send data to the drone.
  • visualize_data_tab(): Visualizes pertinence functions and rules in a tabular format.

Usage:

This class provides an interactive interface for monitoring and controlling the drone.

MQTTClient Class

File: mqtt/mqtt_client.py

The MQTTClient class handles MQTT communication for publishing and subscribing to topics.

Key Methods:

  • __init__(broker, topics): Initializes the MQTT client with a broker and topics.
  • connect(): Connects to the broker and subscribes to topics.
  • on_message(client, userdata, msg): Processes incoming messages.
  • publish(topic, data): Publishes data to a specified topic.

Usage:

This class enables communication between the fuzzy control system and the drone via MQTT.

MQTT Utilities

Monitor MQTT Script

File: mqtt/monitor_mqtt.py

This script monitors MQTT topics and prints received messages.

Key Functions:

  • on_connect(client, userdata, flags, rc): Subscribes to topics upon connection.
  • on_message(client, userdata, message): Decodes and displays messages.
  • on_disconnect(client, userdata, rc): Attempts to reconnect when disconnected.

MQTT Test Data Script

File: mqtt/mqtt_test_data.py

This script publishes random test data to MQTT topics for testing.

Key Functions:

  • generate_random_data(topic): Generates random data for altitude and error topics.
  • main(): Publishes data to topics at regular intervals.