A study on a ballast optimization algorithm for onboard decision support system
Because there are only a limited number of means of action that are available for the master to pursue in the event of flooding, onboard decision support system has been required. The majority of systems activated during a flooding emergency (such as watertight and semi-watertight doors, bulkhead valves, dewatering pumps etc.) almost exclusively aim to restore a sufficiently high level of subdivision to prevent flooding from spreading through the ship. Even though assuming the flooding scenario is not catastrophic, the use of ballast tanks can be an additional and very effective tool to ensure both prevention of flooding spreading and also improve ship stability. This paper describes an optimization algorithm devised to choose the set of ballast tanks that should be filled in order to achieve an optimal response to a flooding accident.
This paper is devoted to the general problem of reconstructing the cost from the observation of trajectories, in a problem of optimal control. It is motivated by the following applied problem, concerning HALE drones: one would like them to decide by themselves for their trajectories, and to behave at least as a good human pilot. This applied question is very similar to the problem of determining what is minimized in human locomotion. These starting points are the reasons for the particular classes of control systems and of costs under consideration. To summarize, our conclusion is that in general, inside these classes, three experiments visiting the same values of the control are needed to reconstruct the cost, and two experiments are in general not enough. The method is constructive. The proof of these results is mostly based upon the Thom's transversality theory.