D&C Lab
Research Activities
The Decision and Control Laboratory (D&C Lab) is dedicated to advancing both theoretical and applied research in systems, control, optimization, and decision-making. Its mission is to contribute to scientific progress and technological innovation by engaging with public institutions and private enterprises at the regional, national, and international levels.
The D&C Lab’s work aligns with the disciplinary sector “Systems and Control Engineering” (09/G1), with a particular emphasis on fostering technology transfer and the dissemination of research outcomes across academic and industrial domains.
The laboratory is based on the university campus in Bari and operates within a multidisciplinary framework. Research and experimental activities are organized across the following main thematic areas:
1. Management and Control of Complex Systems
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Development of advanced algorithms and ICT solutions for proactive decision-making in domains such as energy, transport, production, and healthcare
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Decentralized and distributed control methods for large-scale interconnected systems
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Optimization and supervisory control of complex processes and infrastructures
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Decision support systems for intelligent transportation, multimodal logistics, and hazardous freight operations
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Control strategies for smart mobility and the management of smart environments
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Frameworks for the design and governance of smart grids, smart cities, and smart communities
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Strategies for sustainable, intermodal, and co-modal mobility
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ICT-based solutions for logistics, production, and health service management
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Modeling, simulation, and control of discrete event systems
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Nonlinear system modeling and control
2. Modeling, Control, and Optimization in Industrial Contexts
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Methodologies supporting Industry 4.0 paradigms
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Re-engineering and automation of industrial processes
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Coordination strategies for multi-agent systems and sensor networks
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Fault detection, isolation, and recovery mechanisms
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Optimization of logistics, production, and distribution chains
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Scheduling, workflow management, and decision support in manufacturing systems
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Model-based techniques to enhance technological product/process efficiency
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Decision-making under uncertainty and large-choice scenarios
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Management of procurement and supply networks
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Integration of best practices in advanced manufacturing
3. Management, Control, and Optimization of Energy Systems
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Strategic level: Development of analytical and decision-support tools for urban policymakers focused on long-term energy efficiency strategies. Application domains include building and building grid sectors, public lighting systems, and integrated urban energy systems
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Operational level: Control and scheduling strategies for smart energy users, optimization frameworks for smart homes and smart home networks, and solutions for the optimal charging of electric vehicles