Modal Intervals and Control Engineering (MiceLab)
The imprecision and the uncertainty of complex systems can be represented in many cases by interval models. The core of our research is to develop methods and tools based on interval analysis to deal with this kind of systems.
Research areas:
- Theoretic development of Modal Interval Analysis
- Management of interval uncertainties
- Interval Simulation
- Linear interval systems
- Development of tools for interval computations
- Modal Interval Libraries
- Minimax and optimization algorithms
- Quantified Set Inversion
- Application of interval Methods to Systems and Control
- Robust control analysis and design
- CACSD for Robust Control
- Model-based Predictive Control
- Model-based fault detection and diagnosis
Application Fields:
- Process Engineering Systems
- Chemical/Petrochemical manufacturing processes
- Civil & Mechanical Engineering
- Structural Control
- Structural Health monitoring
- Robotics
- Mobile Robots
- Biomedical applications
- Development of glucemic predictive models
- Insulin dosage-aid systems
- Computer Graphics
- New rendering algorithms based on MIA