Research Topic

Our research aims to explore theories and techniques for the pursuit of a strong adaptivity in smart and complex system. Result of this research include several scientific papers (see our publication page) and a middleware for the implementation of adaptive workflows: MUSA.

Problem

The Shipboard Power System (SPS) is responsible for supplying energy to various services of a vessel. The proper functioning of the SPS is critical to the survival and safety of the ship.

The SPS reconfiguration consists in a variation of the electrical topology to successfully supply energy to critical services. SPS reconfiguration is a relevant problem because many accidents occurring during ship navigation are often due to electrical failures.

Motivation

In recent years, the maritime sector is highlighting a high value of innovative and technological content (ICT), especially when faced with the need to respond to objectives such as safety, efficiency, and environmental impact.

”EMSA’s annual overview of 2015 marine casualties and incidents” reports that most of the accidents mentioned are due to loss of control or damage to ships or equipment. The ship power production and distribution failures play a relevant role in such incident scenarios.

 

The Proposed Self-Adaptive Approach

The proposed reconfiguration procedure uses a distributed and mission-oriented approach,

and it employs a generic-purpose self-adaptive middleware (MUSA). MUSA has been customized to dynamically reconfigure an SPS in case of failures or unexpected events. It allows obtaining a run-time solution that properly considers ship’s mission and current scenario. We also implemented an experimental setup including a Matlab/Simulink simulation of a case study from literature, to validate the solution and to assess our approach.

The approach embraces dynamic goals, non-functional requirements, norms, and QoS. Basing the solution onself-adaptation provides an elegant framework for assessing: 1) flexibility to internal/external changes and failures, 2) reasoning with uncertainty and partial satisfaction of goals, while 3) considering norms and human factors.

The reconfiguration layer is the core of the architecture in which sensorial data are processed in order to discover solution strategies, to present them to the command layer, and finally enact the selected solution. In particular, MUSA provides the facility to perform a qualitative planning, whereas Simulink evaluates each solution from a physical point of view. In line with shipboard regulations, the commander is up to take strategic decisions, supported by a decision support system.

Case Study

The solution we propose is based on a dynamic description of the vessel’s missions. When the system power is under the value required for feeding all the vessel’s loads, the SPS reconfiguration must consider that not all the goals are equally important to be pursued. Indeed, some loads are mandatory for the vessel survivability [vital loads] while other ones are also important but not necessary [semi-vital loads]. Finally, other loads may be switched off without affecting ship mission accomplishing [non-vital loads].