blog banner desktop image blog banner mobile image

6-DoF Modelling and Control of a Remotely Operated Vehicle

In order for ROVs to operate effectively in a range of applications, they need accurate navigation and control systems for easy maneuvring and station keeping. In this thesis, Wu designs and develops a 6-DoF control system for the BlueROV2 Heavy using both a conventional PID controller and a nonlinear model-based PID controller. Wu then examines and compares the performance of both controllers.

Abstract: Remotely Operated Vehicles (ROVs) are today commonly deployed in a range of underwater applications, including offshore oil and gas, defence, aquaculture and scientific research, mostly for inspection and intervention roles. In order to meet the requirements for these roles and operate underwater effectively, the vehicles need accurate navigation and control systems to allow the vehicle to manoeuvre and maintain station with little effort from the operator.

This master’s thesis is concerned with two major phases: the first is modelling and system identification of an observation class mini ROV, named BlueROV2 Heavy; and the second is the design and development of a 6-DoF robust control system for this vehicle. Modelling and system identification comprises mathematical modelling and the subsequent estimation of the relevant parameters. The modelling of the BlueROV2 Heavy was carried out in 6-DoF and consists of developing the thruster model and the dynamic model of motion of the vehicle. A system identification approach of immersion tank testing with the use of on-board sensors is proposed for parameter estimation where the unknown parameters are estimated from the experimental data utilising the least squares algorithm. Due to unforeseen delays in receiving the BlueROV2 Heavy in time, these experiments could not be performed. Instead, the unknown parameters are currently determined by utilising the BlueROV2 Heavy’s technical specifications in combination with published data of the BlueROV.

The determined model from the system identification process was utilised to design the 6-DoF control system for BlueROV2 Heavy in which a conventional PID controller and a nonlinear model-based PID controller were applied, respectively. The thesis examines and compares the performance of both controllers from results of simulations where the nonlinear model-based control system achieves significant improvement in accuracy especially when external disturbance is applied or when multiple movements or rotations are required. Monte Carlo method was applied to analyse the robustness of both control systems in consideration of random disturbances and uncertainties in the process model. The simulation results demonstrate that the designed 6-DoF nonlinear model-based control system is feasible to be implemented on the BlueROV2 Heavy.

Author: Wu, Chu-Jou

Journal: Flinders University

To read more, click here!