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Motion control of underwater robotic vehicles is a demanding task with greatchallenges imposed by external disturbances, model uncertainties andconstraints of the operating workspace. Thus, robust motion control is still anopen issue for the underwater robotics community. In that sense, this paperaddresses the tracking control problem or 3D trajectories for underactuatedunderwater robotic vehicles operating in a constrained workspace includingobstacles. In particular, a robust Nonlinear Model Predictive Control (NMPC)scheme is presented for the case of underactuated Autonomous UnderwaterVehicles (AUVs) (i.e., vehicles actuated only in surge, heave and yaw). Thepurpose of the controller is to steer the underactuated AUV to a desiredtrajectory with guaranteed input and state constraints within a partially knownand dynamic environment where the knowledge of the operating workspace isconstantly updated on-line via the vehicle's on-board sensors. In particular,by considering a ball that covers the volume of the system, obstacle avoidancewith any of the detected obstacles is guaranteed, despite the model dynamicuncertainties and the presence of external disturbances representing oceancurrents and waves. The proposed feedback control law consists of two parts: anonline law which is the result of a Finite Horizon Optimal Control Problem(FHOCP) solved for the nominal dynamics; and a state feedback law which istuned off-line and guarantees that the real trajectories remain bound in ahyper-tube centered along the nominal trajectories for all times. Finally, asimulation study verifies the performance and efficiency of the proposedapproach.

Robust Trajectory Tracking Control for Underactuated Autonomous Underwater Vehicles