Control System Packer is a lightweight, low-level program to transform energy equations into the compact libraries for control systems. Packer supports Python 🐍, C 💻 and C++ 💻libraries.

• Control System Packer
  • Features
  • Why is our project useful and better than the existing solutions?
  • Supported languages
  • Getting Started
    • Cloning a repository
    • Importing phase
      • Python
    • Initialization of your system
    • Getting lagrange equations
      • C
      • C++
      • Python
  • Development
  • Technical stack
  • Glossary
  • Further Development
  • License

• Input the energy equations and get a compact library for the chosen language.
• Parametrize the system for usage with different parameters
• Get a control system out of robot's physical equations

Our goal is to make the lives of robotics developers easier, so you can just type in the energy equations and obtain ready-to-use libraries. You can import them straight away into the robot for the control!

• Our system works with any mechanical model. Every model has it's own general positions and energy equations.
• Most of the programmers used to code and transform these equations manually, there was no popular tool to solve this issue.
• Complex control tasks are done in high-level PLs (such as Python), but low-level computers usually work this C or C++. We provide fast and easy transition from Python to C or C++.

Packer now supports 3 types of the language libraries:

• Python - Python libraries
• C++ - C++ libraries
• C - C headers

1. Open the command line interface
2. Using the command line, access a folder in which you want your project to be saved
3. Type in:

git clone https://github.com/mirnanoukari/Control-System-Packer.git

Then, you need to import Mechanicalsystem class from euler_lagrange to your mechanical system, use one of our examples in the example folder

from lib.symbolical_dynamics.euler_lagrange import MechanicalSystem

name_of_your_system = MechanicalSystem(q,K,P,R)

• q (generalized coordinates)
• K (kinetic energy)
• P (potential energy)
• R (rayleigh dissipative function)

Or you can assign values to your mechanical system using set functions:

name_of_your_system = MechanicalSystem(q)
name_of_your_system.set_kinetic_energy(K)
name_of_your_system.set_potential_energy(P)
name_of_your_system.set_rayleigh(R)

name_of_your_system.get_lagrange_equations(simp=True)

The model then produces an equation, and results a combined terms of potential energy and inertia matrix.

Great! Now, your system is initialized with values. You can use them both in Python, C and C++ Below we present the usage of both cases.

print(f'\nEquations of motion:\n{name_of_your_system.Q}')
print(f'\nInertia matrix:\n{name_of_your_system.D}')
print(f'\nGeneralized momenta:\n{name_of_your_system.p}')

First of all, we should generate headers from Python code:

name_of_your_system.get_headers()

Now you can simply import these headers, and use built-in functions to find exact value for any numerical arguments:

#include "numerical_combined.h"
#include <stdio.h>
int main(void) {
   double result[2] = {0}; // initialize the array to store the result
   numerical_combined(2,3,4,5,6,7,8,9,0,12,21,result);  // Example of usage of generated headers
   printf("%d", result[0]);
   return 0;
}

In your python file, set create_cpp to True and generate an optional cpp class file (euler_lagrange.cpp) which will include all our headers in it:

numerical_combined.get_headers(create_cpp=True)

The file euler_lagrange.cpp will contain ready-to-use functions, and you can import it in your code:

#include "euler_lagrange.cpp"

Want to contribute? Check out our contribution policy

• Python 🐍
• SymPy (Python) 🧮
• PyBind (Python) 📚
• Setuptools (Python) 🔧
• C 🖥️
• C++ 💻
• Markdown📃

Packer - a program that allows you to turn input (energy equations) into compact libraries for various programming languages.

Control system - a system, which provides the desired response by controlling the output.

Header - a file containing C language declarations and macro definitions to be shared between several source files.

Library - a collection of non-volatile resources used by computer programs for software development.

Energy equations - potential and kinetic energies equations in symbolic format.

Method of Lagrange multipliers - strategy for finding the local maxima and minima of a function subject to equality constraints.

At the moment, the development of a reverse conversion to Python is underway, using cython and the PyBind library. It is planned to compare the execution speeds of methods in C ++ and in Python.

We are also working on uploading this package to PyPI so that it will be an official package to use for everyone.

MIT

Free Software, Hell Yeah!