The mission of the Decision and Control Laboratory (D&C Lab) is to conduct theoretical and applied research in the broad areas of systems, control, optimization, and decision-making.
Major objectives are the promotion of the results obtained in the field of the scientific research - achieved in collaboration with private and public partners - in a regional, national, and international context, and the advancement of technology transfer of these research results.
The main areas of interest for the research are the scientific disciplinary sector of “Systems and control engineering” (09/G1).
The laboratory is located inside the university campus in Bari.
Research and experimentation activities at D&C Lab are conducted in the following macro-areas:
* Management and control of complex systems
Advanced algorithms and ICT applications to predict and solve upcoming situations in various applicative contexts (energy, transport, production, health systems) with minimal or reduced human involvement
Decentralized and distributed control and optimization for large scale systems
Management, control, and optimization of complex systems
Decision support systems for planning and management of Intelligent Transportation Systems, road and rail-road traffic, dangerous freight transport
Management and optimization of smart environment and smart mobility
Design and governance of smart grids, smart cities, and smart communities
Sustainable mobility, multimodal, intermodal, and co-modal transportation
ICT for logistics, manufacturing, and healthcare systems
Modelling, simulation, optimization, and control of discrete event systems
Modelling and nonlinear control
* Modelling, control and optimization of industrial applications
Re-engineering and automation of manufacturing processes and systems
Coordination of agents and sensors networks
Fault detection and recovery
Logistics, production and distribution
Scheduling and planning, workflow management
Models for maximizing the effectiveness of technological products and processes
Methods for the reduction of alternatives, particularly in the case of large amount of choices
Supply and purchasing management
Best practices in manufacturing
* Management, control and optimization of energy systems
Strategic level: analysis and decision tools to support the urban policy maker in determining optimal action plans for long-term energy efficiency in the following areas: building and building grids sectors, public street lighting sector, and integrated management of urban energy systems
Operational level: solutions for the control and scheduling of the energy activities of smart energy users, optimal planning of the energy activities of a smart home, networks of smart homes, management of the optimal charging of electric vehicles