Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)

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Fuzzy Genetic Algorithm Based Antilock Braking System

Authors
Srinivasa Rao Gampa1, Kiran Jasthi1, Sireesha Alapati1, Satish Kumar Gudey2, *, Valentina E. Balas3
1Seshadri Rao Gudlavalleru Engineering College, Gudlavalleru, 521356, A.P., India
2Gayatri Vidya Parishad College of Engineering, Visakhapatnam, 530048, A.P., India
3Aurel Vlaicu University of Arad, Arad, Romania
*Corresponding author. Email: satishgudey13@gmail.com
Corresponding Author
Satish Kumar Gudey
Available Online 5 December 2022.
DOI
10.2991/978-94-6463-074-9_3How to use a DOI?
Keywords
Anti lock braking system; fuzzy logic controller; genetic algorithm; predicted slip
Abstract

In this paper a fuzzy genetic algorithm based anti lock braking system is designed for generating optimum braking torque for vehicles during braking conditions. In this work two fuzzy controllers are used, the first one for road condition estimator and the second is braking torque controller. The fuzzy road condition estimator takes slip ratio and present braking torque as inputs and predicts the road condition. The fuzzy braking torque controller takes present braking torque, current slip, predicted slip and road condition as inputs and generates the braking torque to be applied for next stage. The auto regressive model is used for predicted slip modeling. The braking torque gain of the fuzzy controller and the parameters of the predicted slip model are obtained using genetic algorithm considering optimum stopping distance as the objective function.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
5 December 2022
ISBN
10.2991/978-94-6463-074-9_3
ISSN
2589-4919
DOI
10.2991/978-94-6463-074-9_3How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Srinivasa Rao Gampa
AU  - Kiran Jasthi
AU  - Sireesha Alapati
AU  - Satish Kumar Gudey
AU  - Valentina E. Balas
PY  - 2022
DA  - 2022/12/05
TI  - Fuzzy Genetic Algorithm Based Antilock Braking System
BT  - Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)
PB  - Atlantis Press
SP  - 13
EP  - 22
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-074-9_3
DO  - 10.2991/978-94-6463-074-9_3
ID  - Gampa2022
ER  -