Remotely Operated Vehicles (ROV) are widely utilized within the maritime industry, including oil and gas exploration, security, and in environmental protection duties. However, designing proper controller systems for ROVs is not an easy task due to the nonlinear dynamic effects and environmental disturbances. This paper describes the development of a self-tuning nonlinear PID controller for an observation class ROV consisting of three thrusters. The proposed algorithm differs from conventional PID control systems, and mimics the principle of neural cells whose parameters have the ability to adapt to the uncertainty of the controlled system. To verify the effectiveness of the nonlinear PID control algorithm, a mathematical model of the ROV incorporating hydrodynamic coefficients obtained through Computational Fluid Dynamics (CFD), is used to compare the performance of a conventional PID controller to that of the proposed nonlinear PID controller.
History
Publication title
Proceedings of the Second Vietnam Conference on Control and Automation
Editors
Cat, PT
Pagination
1-8
Department/School
Australian Maritime College
Publisher
University of Da Nang
Place of publication
Da Nang, Vietnam
Event title
The Second Vietnam Conference on Control and Automation