Git Product home page Git Product logo

pid-pida-gatuning's Introduction


Logo

View PID GA Tuning Toolbox on File Exchange GitHub top language GitHub release (latest by date) License

PID, PI-D, I-PD and PIDA genetic algorithm parameters optimization made easy with this GUI!
Explore the docs »

View Demo · Report Bug · Request Feature

final_gui


Table of Contents
  1. About
  2. Features
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments

About

The PID GA Tuning Toolbox is a powerful tool for tuning the parameters of PID, PI-D, I-PD, and PIDA controllers using genetic algorithms. It has been extensively used in the development of the article titled A comparison between PID and PIDA.

The tuning of the controllers is determined with genetic algorithms by minimizing the integrated absolute error. Both the set-point following and load disturbance rejection tasks can be selected separately. In order to provide a fair comparison, a constraint on the maximum sensitivity is also posed, by selecting between 1.4 and 2 so that the achieved robustness is taken into account.

The PID GA Tuning Toolbox is a valuable resource for achieving optimal controller performance and robustness. It provides a basis for conducting comparative studies, as demonstrated in the referenced article.

(back to top)

Features

The PID GA Tuning Toolbox includes the following features:

  • Controller Selection: Choose from four different controllers.
  • Control Task: Opt for either setpoint following or load disturbance rejection.
  • Process Compatibility: Compatible with any type of process.
  • User-Friendly GUI: Utilize a simple graphical user interface (GUI) to visualize simulation results, including process variable, control action, Bode plot, and Sensitivity plot.
  • Result Evaluation: Easily assess step response and Bode plot characteristics for effective tuning.

(back to top)

MATLAB® Toolbox Installation

Follow the steps below to install FEATool as a MATLAB® toolbox, and to enable running MATLAB® simulation m-scripts

  1. Download the GA_PID_tuning.mlappinstall toolbox installation file.

  2. Then start MATLAB®, press the APPS toolbar button, and select the Install App button.

  3. When prompted to choose a toolbox file to install, select the GA_PID_tuning.mlappinstall file and press OK.

  4. Press the Install button if prompted to "Install to My Apps".

Once the toolbox has been installed, an app icon will be available in the APPS toolbar to start the GA_PID_tuning GUI. (Note that MATLAB® may not show or indicate the toolbox installation progress or completion.)

installation

(back to top)

Basic Use

To effectively utilize the PID GA Tuning Toolbox, follow these simple steps:

  1. Controller Selection: Choose the type of controllers you want to tune.

  2. Process Model: Insert the process model by separating each coefficient with a comma and press the Insert Transfer Function. You can verify your transfer function to ensure correct insertion.

  3. Maximum Sensitivity: Select the maximum sensitivity between 1.4 and 2 for enhanced robustness.

  4. Task Optimization: Choose your task optimization between Setpoint Following and Load Disturbance Rejection based on your control requirements.

  5. Algorithm Parameters: Configure the Population Size and the Maximum Generation as needed for your tuning process.

  6. Start Simulation: Finally, press Start Simulation to begin the tuning process.

These straightforward steps will help you make the most of the PID GA Tuning Toolbox for your controller parameter optimization needs.


Demo

Demo.basic.usage.mp4

(back to top)

License

Distributed under the MIT License. See LICENSE.txt for more information.

(back to top)

Contact

(back to top)

Documentation

PID Controller


PI-D Controller


Proportional and Integral action is applied to the control error while Derivative action is applied to the process variable.

I-PD Controller


Integral action is applied to the control error while Proportional and Derivative action is applied to the process variable.

PIDA Controller


pid-pida-gatuning's People

Contributors

edogitmira avatar marco-milanesi avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.