Underwater vehicles that use differential thrust for surge and yaw motion control have the advantage of increased maneuverability. Unfortunately, such vehicles usually don’t have thrusters/actuators to control the lateral movements. Hence, they fall into the underactuated
vehicle category.
The goal of the work in this thesis is to develop an autonomous control system for a differential thrust underwater remotely operated vehicle (ROV) to track predefined position trajectories. This is challenging because the mathematical model for underwater vehicles is highly nonlinear and the environmental disturbances are usually strong and unpredictable. These factors make the design of the control system very difficult.
In this work, we use the VideoRay Pro III micro ROV as the test platform, on which we design an autonomous control system. We first present the development and analysis
of a hydrodynamic model of the VideoRay Pro III using both analytical and experimental approaches. Based on this model, a state estimator is then designed using the unscented Kalman filter, which yields better estimates of the system states and their uncertainty level in a highly nonlinear system than the commonly used extended Kalman filter. In the controller design, the integrator backstepping technique is used to achieve a Lyapunov stable trajectory tracking controller based on the work by A. P. Aguiar et al. We extended their work by further considering the quadratic drag terms in the vehicle’s hydrodynamic model. The sliding mode control is used to design the bearing and depth controller.
Finally, the autonomous control system is validated by simulation and experimental tests. It is shown that the VideoRay Pro III is able to track the predefined trajectory
within error range of 0.5 meters.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/2683 |
| Date | 22 January 2007 |
| Creators | Wang, Wei |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | 2001342 bytes, application/pdf |
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