Self-Organizing Neuro-Fuzzy Control for Underwater Robotic Vehicles.

Authors

A. Yassien, Computer and System Department.,Faculty of Engineering., El-Mansoura University., Mansoura., Egypt
Mohamed Sherif ElKasas, Computer and System Department., Faculty of Engineering., El-Mansoura Univeersity., Mansoura., Egypt
Sabry Saraya, Computer and System Department., Faculty of Engineering., El-Mansoura University., Mansoura., EgyptFollow
M. El-Basyouni, Faculty of Specific Education., El-Mansoura University.

Corresponding Author

Saraya, Sabry

Subject Area

Computer and Control Systems Engineering

Article Type

Original Study

Abstract

Underwater robotic vehicles have become an important tool for various underwater tasks because they have greater speed, endurance and depth capability, as well as a higher factor of safety, than human divers. However, most vehicle control system designs have been based on a simplified vehicle model, which has often resulted in poor performance because the nonlinear and time-varying vehicle dynamics lave parameters uncertainty. It is desirable to have an advanced control system with the capability of learning and adapting to change in the vehicle dynamies and parameters. The proposed system is possessing neural network's learning ability. There are no rules initially in the proposed system. They are created and adapted as on-line leaning proceeds via simultaneous structure and parameter identification. The identification process of the controller includes both structure and parameter learning.

Recommended Citation

Yassien, A.; ElKasas, Mohamed Sherif; Saraya, Sabry; and El-Basyouni, M. (2021) "Self-Organizing Neuro-Fuzzy Control for Underwater Robotic Vehicles.," Mansoura Engineering Journal: Vol. 27 : Iss. 1 , Article 2.
Available at: https://doi.org/10.21608/bfemu.2021.142440