Motor Control System

A Python-based CAN motor control system featuring a real-time GUI interface for precise position control and monitoring.

Overview

This project provides a comprehensive solution for controlling and monitoring CAN-based motors with features including:

• Real-time position and velocity monitoring
• Interactive GUI control panel
• Dynamic motion parameter adjustment
• Real-time data visualization with auto-scaling charts
• Comprehensive logging system

Prerequisites

• Python 3.8 or higher
• CAN interface hardware
• Linux operating system (for CAN support)

Installation

1. Clone the repository:

git clone https://github.com/yourusername/motor-control-system.git
cd motor-control-system

2. Install required packages:

pip install -r requirements.txt

Project Structure

• MultiMotorControl_PP.py: Core motor control implementation
• motor_control_gui.py: GUI implementation
• requirements.txt: Python package dependencies
• LICENSE: MIT license file

Usage

1. Configure CAN interface:

sudo ip link set can0 type can bitrate 1000000
python eRobControl_PP.py
python MultiMotorControl_PP.py

Features

Motor Control

• Position control with angle input
• Velocity, acceleration, and deceleration parameter adjustment
• Real-time position and velocity monitoring

GUI Interface

• Real-time position and velocity plots
• Auto-scaling axes for optimal data visualization
• Operation logging panel
• Parameter input validation

Data Visualization

• Dynamic chart scaling
• 10-second time window display
• Dual-axis display for position and velocity
• Anti-aliased rendering

Configuration

Default motor parameters:

• Encoder resolution: 524288 pulses/revolution
• Default velocity: 5°/s
• Default acceleration: 5°/s²
• Default deceleration: 5°/s²

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a new Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Authors

[Your Name] - Initial work

Acknowledgments

• PyQt5 team for the GUI framework
• python-can developers for CAN support
• CANopen community for protocol implementation