Laboratorio di Identificazione e Controllo dei Sistemi Dinamici Dipartimento di Ingegneria Industriale e dell'informazione

Transcription

1 Laboratorio di Identificazione e Controllo dei Sistemi Dinamici Dipartimento di Ingegneria Industriale e dell'informazione Laboratorio di Identificazione e Controllo dei Sistemi Dinamici 4 Professors G. De Nicolao, A. Ferrara, L. Magni, D.M. Raimondo 1 Assistant professor C. Toffanin 1 Lab technician G. De Felici Post-docs & Ph.D. students

2 Projects Automazione: progetti Fields - Industrial automation: robotics, diagnostics in semiconductor manufacturing - Energy production: control of power systems, microgrids, wind farms, batteries - Automotive: modelling and control of motors and vehicles - Pharmaceutics: modelling and simulation of pharmacological effects - Biomedicine: artificial pancreas, modelling of cell populations 2

3 Collaboration with Companies o Fedegari Autoclavi S.p.A.: Identification of autoclave models for simulation environment; virtualization of industrial processes including robotic systems for simulation and assessment. o Brambati S.p.A.: Model identification for monitoring and control of roasting plants. o Stelar S.r.l.: magnetic field control for magnetic resonance devices 3

4 Artificial Pancreas o Glucose control in Type 1 diabetes patients o MPC controller o Clinical trials o Model identification of real patients o Automatic adaptation of the controller 4

5 Industrial, Mobile and Service Robotics, Robotics & Artificial Intelligence o Collaborations with companies: Fedegari SpA and SINTA - Sistemi Integrati di Automazione Srl (possibilities for thesis and internships) o Collaborations with Control Systems Technology Group, Eindhoven University of Technology 5

6 Automotive Control, Autonomous Driving and Road Traffic Control Traction Control for racing cars, ABS, ESP, ADAS (advanced driver-assistance systems) Braking and Traction Control for motorbikes o Collaboration with CRF - Centro Ricerche FIAT (possibilities for thesis and internships) o Collaborations with: Advanced Vehicle Engineering Group, University of Surrey, UK, Centre for Mobility Transport, University of Coventry, UK, KTH Stoccolma, Sweden, INRIA, Grenoble, France, TU-Delft, The Netherlands, University of Seville, Spain o Collaboration with Automotive Engineering Department, Ilmenau University of Technology, Germany (European Project ITEAM on control of multi-actuated vehicles in progress) o Contacts in McLaren, Jaguar, Volvo, Skoda o Former collaborations with Ferrari F1, Daimler-Chrysler (now Daimler AG), FIAT, MAN 6

7 Power Systems e Smart Grids Control o Power Systems state estimation and control o Microgrids control: islanded microgrids (voltage control and power flow optimization) o Microgrids control: grid-connected microgrids (current control) o Collaboration with University of Groningen, The Netherlands o Collaboration with University of Exeter, UK o Collaboration with Università di Genova (Savona Campus) o Collaboration with Scuola Politecnica e delle Scienze di Base, Università degli Studi della Campania Luigi Vanvitelli (Control of DC microgrids in airplanes) 7

8 Stochastic optimal power flow Renewable energy production is considered as a key step to create environmentally friendly energy systems and consequently less dependent on fossil fuels. However, the high penetration of renewable generators (wind, solar) into the grid is challenging due to the intermittent availability of these sources. What we did: Stochastic Optimal Power Flow (OPF) Usage of Energy Storage Systems Loads Curtailment Electric load forecasting Possible activities: Implement the ability to shift the loads in time (demand response) Use more accurate battery models in the context of OPF. 8

9 Model-based control of Lithium-ion Batteries Battery Electric Vehicles are the future. The battery pack of a Tesla Roadster contains around 7000 lithium ion cells, arranged into parallel and series connections. Battery management systems are required to guarantee safety, fast charging and slow ageing in Li-ion batteries. What we did: LIONSIMBA, a Matlab framework that numerically implements the well known P2D model equations, in order to simulate, design and control Liion cells. Future activities: Collaboration with: Massachusetts Institute of Technology Imperial College of London Simulate and control the whole Tesla battery Aging modeling of the Li-ion battery pack Optimum experimental design for parameters estimation Collaboration with Imperial College of London and University of Konstanz 9

10 Industry 4.0 EU Project Power Semiconductor and Electronics Manufacturing 4.0. In collaboration with Self navigation system for a robotic fleet Optimal energy Management of Heating, Ventilation and Air Conditioning systems Activities Optimal dispatching of several wafers among several robots Advanced tracking control techniques Collision avoidance Activities Plant modelling and monitoring Data extraction, analysis and forecasting Optimization and control strategies 10