In this paper, we investigate the problem of setpoint stabilization and station keeping for Remotely Operated Underwater Vehicles. Manual control of such vehicles is a difficult task, due to environmental disturbances and complexity of the dynamics. The development of automatic control schemes to achieve station keeping and setpoint stabilization is complicated by the lack of precise information regarding the position, velocity and attitude of the vehicle with respect to an inertial reference. We propose a methodology for robust control design of a specific ROV model, which combines sensor information from sources of heterogeneous kind, namely a monocular CDD camera, a yaw compass, a depth sensor, and an inertial platform. The main feature of our approach is the incorporation in the controller structure of a suitable model of the disturbances, which reduces the tmcertainty in the vehicle attitude and position determination. The proposed approach is applied to the problem of robust station keeping of a specific model of a small commercial ROV, employed for pipeline inspection and maintenance of submerged offshore structure. Simulations performed on a 4 degrees-of-freedom model of the specific ROV show that the method is well suited to cope with imprecise sensor information and with environmental disturbances due to underwater current effects.
A crucial problem in underwater automation is given by the scarcity of proper sensor information, especially regarding the real-time position of the vehicle with respect to a reference frame. A number of heterogeneous pieces of information (available at different sampling rates) must be made available to the control authority. As an example, typical information on the vehicle position come from CCD cameras, sonar and ultrasonic transponders, while information of the vehicle attitude are generally retrieved from compasses and rate gyros. In an underwater environment, the performance of these sensors, in terms of accuracy and bandwith, may be quite poor: for instance, signals available from sonar are available only at a very slow sampling rate. Signals from CCD cameras have a narrow bandwidth, and should not be differentiated to retrieve the vehicle velocity to avoid delays and high levels of noise in the control loop. On the other hand, signals from rate gyros and inertial platforms must be integrated to recover vehicle velocity and angular velocity, but this necessarily induces offsets and drifts in the measurements. The goal of this paper is to employ methodologies from nonlinear regulation theory to obtain sensor fusion and achieve setpoint control for a general model of small commercial ROVs. Our approach is to employ internal models of sensor drifts and disturbances to obtain sensor fusion directly at the controller level, rather than at the coordination level (that is, the guidance system) of the control authority. Moreover, internal model-based control is shown to improve the capability of the control system to reject environmental disturbances such as the underwater current. Besides the methodological contribution, our approach allows to endow the control and guidance scheme for ROVs with enhanced station-keeping capabilities.