Modeling and Motion Control Strategy for AUV

Autonomous Underwater Vehicles (AUV) speed and position control systems are subjected to an increased focus with respect to performance and safety due to their increased number of commercial and military application as well as research challenges in past decades, including underwater resources exploration, oceanographic mapping, undersea wreckage salvage, cable laying, geographical survey, coastal and offshore structure inspection, harbor security inspection, mining and mining countermeasures (Fossen, 2002). It is obvious that all kinds of ocean activities will be greatly enhanced by the development of an intelligent underwater work system, which imposes stricter requirements on the control system of underwater vehicles. The control needs to be intelligent enough to gather information from the environment and to develop its own control strategies without human intervention (Yuh, 1990; Venugopal and Sudhakar, 1992). However, underwater vehicle dynamics is strongly coupled and highly nonlinear due to added hydrodynamic mass, lift and drag forces acting on the vehicle. And engineering problems associated with the high density, non-uniform and unstructured seawater environment, and the nonlinear response of vehicles make a high degree of autonomy difficult to achieve. Hence six degree of freedom vehicle modeling and simulation are quite important and useful in the development of undersea vehicle control systems (Yuh, 1990; Fossen 1991, Li et al., 2005). Used in a highly hazardous and unknown environment, the autonomy of AUV is the key to work assignments. As one of the most important subsystems of underwater vehicles, motion control architecture is a framework that manages both the sensorial and actuator systems (Gan et al., 2006), thus enabling the robot to undertake a user-specified mission. In this chapter, a general form of mathematical model for describing the nonlinear vehicle systems is derived, which is powerful enough to be applied to a large number of underwater vehicles according to the physical properties of vehicle itself to simplify the model. Based on this model, a simulation platform “AUV-XX” is established to test motion characteristics of the vehicle. The motion control system including position, speed and depth control was investigated for different task assignments of vehicles. An improved Ssurface control based on capacitor model was developed, which can provide flexible gain selections with clear physical meaning. Results of motion control on simulation platform “AUV-XX” are described.