Improving the Performance of Kalman Filter in PID Control Systems Using Neural Networks and Genetic Algorithms

Authors

  • ahmed Ali Tishreen university
  • Mohsen Daoud Tishreen University

Abstract

This article provides a study to enhance the performance of a control system, specifically the system relying on a PID (Proportional-Integral-Derivative) controller with a Kalman filter, by incorporating artificial intelligence techniques (genetic algorithm and artificial neural network) into the previous system. The research aims to analyze and evaluate the performance of the proposed system compared to the traditional PID controller with a Kalman filter. To achieve this, the system was applied to an Autonomous Underwater Vehicle (AUV) and simulations were conducted under ideal conditions (without noise) and in a marine operating environment (with noise).

Simulations were performed and the results were presented using MATLAB software. Simulation results of steering angle control for the vehicle (without noise) showed a decrease in Integral Absolute Error (IAE), overshoot, and settling time by 61%, 28%, and 78.4%, respectively. Meanwhile, simulation results (with noise) exhibited a decrease in IAE and overshoot by 94.9% and 23.5%, respectively. However, the settling time was not achieved in the PID model with a Kalman filter because the noise caused oscillations in the response function beyond the acceptable error range for settling time.

On the other hand, the settling time for the proposed algorithm with similar noise was comparable to the settling time without noise.

Downloads

Published

2024-11-17

How to Cite

1.
علي ا, محسن داود. Improving the Performance of Kalman Filter in PID Control Systems Using Neural Networks and Genetic Algorithms. Tuj-eng [Internet]. 2024Nov.17 [cited 2024Dec.26];46(4):359-75. Available from: https://journal.tishreen.edu.sy/index.php/engscnc/article/view/17520

Issue

Vol. 46 No. 4 (2024): Tishreen University Journal of Research and Scientific Studies - Engineering Sciences Series

Section

Master student researches

License

Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-sa/4.0/

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

The authors retain the copyright and grant the right to publish in the magazine for the first time with the transfer of the commercial right to Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series

 Under a CC BY- NC-SA 04 license that allows others to share the work with of the work's authorship and initial publication in this journal. Authors can use a copy of their articles in their scientific activity, and on their scientific websites, provided that the place of publication is indicted in  Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series   .  The Readers have the right to send, print and subscribe to the initial version of the article, and the title of  Tishreen University Journal for Research and Scientific Studies - Engineering Sciences Series     Publisher

journal uses a CC BY-NC-SA license which mean

You are free to:

  • Adapt — remix, transform, and build upon the material
  •  
  • The licensor cannot revoke these freedoms as long as you follow the license terms.

 

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  • NonCommercial — You may not use the material for commercial purposes.
  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.