Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Offshore Environment

Conference Paper

Title: Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Offshore Environment

Author:

Manikandan, R.

Publication Date:

April 24, 2022

Event Name:

3rd International Conference on Artificial Intelligence: Advances and Applications (ICAIAA 2022)

Event Location:

Jaipur, India

Pages:

69–77

Publisher:

ICAIAA

Affiliation:

Technion Israel Institute for Technology

Collection Method:

Modeling

Engineering:

Control

Document Access

Website:

External Link

Citation

Manikandan, R. (2022). Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Offshore Environment. Paper presented at 3rd International Conference on Artificial Intelligence: Advances and Applications (ICAIAA 2022), Jaipur, India.

@conference{Manikandan-2022-20899,
author = {Manikandan, R},
title = {Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Offshore Environment},
year = {2022},
month = {apr},
series = {3rd International Conference on Artificial Intelligence: Advances and Applications (ICAIAA 2022)},
pages = {69--77},
address = {Jaipur, India},
publisher = {ICAIAA},
url = {https://link.springer.com/chapter/10.1007/978-981-19-7041-2_6},
keywords = {Modeling, Control},
}

Export Citation to BibTex

TY - CONF
TI - Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Offshore Environment
AU - Manikandan, R
T2 - 3rd International Conference on Artificial Intelligence: Advances and Applications (ICAIAA 2022)
C1 - Jaipur, India
AB - Brushlike Direct Current Motors(BLDCM) are the most extensively used machine in a wide range of oceanic applications such as operation of offshore wind turbines, including robotics, food technology, and aviation. PID controllers exceed other linear controllers in terms of performance. This controller is typically utilized for controlling the motor’s speed. In computing, the traditional approach for adjusting PID parameters is indirect. In this paper, two non-traditional algorithms, Genetic Algorithm and Ant Colony Optimization, are proposed for tuning PID parameters in order to control the speed of BLDC motor. With the goal of constructing a speed regulation controller, these algorithms were applied and assessed on a second-order plant model of a BLDC motor. The GA- and PSO-based control algorithms were implemented using MATLAB–Simulink interfaces. For each technique, the resulting system performance was compared.
DA - 2022/04//
PY - 2022
SP - 69–77
PB - ICAIAA
UR - https://link.springer.com/chapter/10.1007/978-981-19-7041-2_6
LA - English
KW - Modeling
KW - Control
ER -

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Abstract

Brushlike Direct Current Motors(BLDCM) are the most extensively used machine in a wide range of oceanic applications such as operation of offshore wind turbines, including robotics, food technology, and aviation. PID controllers exceed other linear controllers in terms of performance. This controller is typically utilized for controlling the motor’s speed. In computing, the traditional approach for adjusting PID parameters is indirect. In this paper, two non-traditional algorithms, Genetic Algorithm and Ant Colony Optimization, are proposed for tuning PID parameters in order to control the speed of BLDC motor. With the goal of constructing a speed regulation controller, these algorithms were applied and assessed on a second-order plant model of a BLDC motor. The GA- and PSO-based control algorithms were implemented using MATLAB–Simulink interfaces. For each technique, the resulting system performance was compared.