Intelligent diving control of a lagrangian type of underwater robot

The SWARM underwater system, which consists of multiple, homogenous robots, is a project for monitoring the Baltic Sea environments. The unit of the system is a Lagrangian type robot which can control its depth by changing the buoyancy using a piston engine, and moves otherwise freely with the sea water flows. The depth control of the robots is very important for the performance of the whole system. This thesis provides an energy optimal diving control algorithm for the SWARM robots to improve the performance and energy consumption of the diving process. Due to the nonlinear environment and dynamics, most of the classical theories may not achieve good results and consume much energy. The environment based depth control algorithm estimates the water density by a density model, which is built from previous information or measurement. By reducing the piston movements, much energy can be saved than the previous control algorithm. The Baltic environments are studied and the physical water properties including salinity, temperature, pressure and density are analyzed. Result proves the availability of the seawater properties model in diving control. Different methods of measuring seawater density and updating the environment model are evaluated, and the environment based control algorithm is tested in the simulator. Error and energy consumption are analyzed and the result shows the diving performance is improved significantly.Validerat; 20101217 (root