Abstract

Autonomous underwater vehicles (AUVs) are essential for marine applications. However, ensuring stable operation in dynamic and uncertain underwater environments remains a critical challenge due to complex hydrodynamic behavior and unpredictable external disturbances. We present a PSO-optimized LQR controller deployed in an underactuated AUV for a depth-tracking problem. The AUV model considers the nonlinearities inherent to the system and the external uncertainties, such as hydrodynamic and environmental uncertainties. A double-loop ALOS-LQR controller coupled with ESO is simulated and compared with the proposed controller. The proposed controller scheme yields faster settling time and lower MAE of the depth tracking error than the double loop strategies.

About the Speaker

Mr. Muhammad Habib received his Bachelor of Engineering degree in Chemical Engineering from the University of Technology Brunei, Brunei Darussalam, in 2018. He is currently pursuing his Ph.D. Degree in Systems and Control Engineering in the Control and Instrumentation Engineering Department at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. His research experience encompasses intelligent control systems, optimization algorithms, and power management, with the focus on the integration of electric vehicles.