Control Systems and Advanced Robotics
Theoretical developments and application of new modeling and control paradigms applied to complex engineering problems. Research will focus on modeling, identification and control of nature inspired systems, modeling of fractional systems, variable order control, modeling and control of processes and buildings, distributed optimization of supply chains using modern control paradigms, and fault-tolerant control in networked control systems based on multi-agents.
Development and application of new methodologies for collaborative and hybrid human/robotic manipulation systems, medical and service robots, biomedical applications, fleets of robotic vehicles in ground, sea and aerial scenarios, flight control and machine vision for industrial applications, medical image processing and robotic intelligent assistance.
Intelligent Automation, Data Modelling and Optimization
New methodologies in automation and systems integration (modular and product development platforms for industry and transports, renewable energy production and management, building automation), systems design in mechatronic systems (integrated design of mechatronic systems in energy, health and industry), environment (forest fires) and civil protection applications, comfort and safety design in transportation), and dynamic simulation of industrial processes and buildings.
Data analysis for prediction, decision making and decision support systems based on intelligent methodologies, distributed optimization using bio-inspired metaheuristics in energy, transports, aerospace, health, manufacturing and logistics, design of intelligent models and algorithms to develop classifiers in health care and process modeling systems.