Genetic algorithm that optimizes PID values to minimize ISE. It can use either Matlab/Simulink or built-in Python model for simulating plant.

• Python 3.6+
• NumPy
• SciPy
• Control
• Matlotlib
• MATLAB Engine for Python
• TKInter

1. Install Python 3.6+
2. Clone this repo
3. Install dependencies:

pip install numpy scipy matplotlib control

4. Go into the repo directory and run main.py

cd GA_PID_Tuner && python main.py

Described here: https://www.mathworks.com/help/matlab/matlab_external/install-the-matlab-engine-for-python.html

Opis większości plików i katalogów w projekcie:

• genetic - Genetic Algorithm reletated files
  • algorithms - Crossover, mutation and selection implementations
• matlab - Matlab and simulink files
  • simulate.m - [function] Simulates model with Simuling
  • simulate2.m - [function] Sumulates model WITHOUT Simulink
  • circuit.slx - Simulink model (Note: watch out the Simulation Parameters)
  • run.m - for testing purposes
• sim - model simulation and fitness calculation
  • AbstractSimModel.py - base class
  • PythonSimulatedModel.py - simulation in Python using Control lib
  • MatlabModel.py - starts Matlab and runs simulate2.m
  • MatlabSimulinkModel.py - Starts Matlab and runs simulate.m + Simulink
• tests - unit tests
• main.py - run this file to start
• config.py - default config
• application.py - UI Interface

By default, a Python built-in model is used for calculating fitness, but there is also Matlab support. To switch model to matlab, do the following:

0. Make sure that you have Matlab Engine for Python installed
1. Check the matlab directory to see how scripts are made
2. Open application.py
3. Add the beginning, add the proper import:

from sim.MatlabModel import MatlabModel
# Or, if you want to use Simulink:
from sim.MatlabSimulinkModel import MatlabSimulinkModel

4. In line 289, change PythonSimulatedModel(cfg) to either MatlabModel(cfg) or MatlabSimulinkModel(cfg)

self.simulation = Simulation(cfg,
                            PythonSimulatedModel(cfg),
                            GeneticAlgorithmImpl(cfg))