Advanced Control and Technologies for Enhanced Mechatronics and Automation (ACTEMA)

Taking the cue from the paradigms of Cyber-Physical Systems (CPS), the ACTEMA research group develops methods and technologies in the field of control, monitoring and diagnosis of innovative mechatronic and automation systems.  

Starting from physics-based modelling techniques, the proposed control solutions are mainly based on nonlinear and adaptive techniques, internal model principle, hybrid systems and input and state constrained control methods. Beside these, identification and machine learning techniques are exploited, in particular for monitoring and diagnosis of systems where standard modelling approaches are not effective.  

In order to achieve an actual implementation of the proposed solutions, the ACTEMA research group also develops innovative hard real-time infrastructures, including software modules and signal/power hardware, where edge and cloud computing are properly mixed.  

In the following, the main activities are reported: 

  • Sensorless control of electric drives based on synchronous and induction motors (PMSM and IM). 
  • Control of Doubly-Fed Induction Machines (DFIM) used as generators in wind turbines.  
  • Control of Active Power Filters (APF) for reducing the harmonic pollution in electric line grids, in particular Shunt Active Filters (SAF).  
  • Study of electric propulsion systems for Unmanned Aerial Vehicles – UAV and other vehicles. 
  • Development of hard real-time embedded platforms, based on heterogeneous multicore processors, oriented to high-performance edge computing for control, monitoring and diagnostic applications. 
  • Study and development of controlled power converters for innovative applications and drives.  
  • Study, modelling and motion control of nonlinear flexible mechanisms, realized by means of Additive Manufacturing (Smart Mechanical Structures).  
  • Study, modelling and control of actuators based on Shape Memory Alloys (SMA). 
  • Modelling, control and diagnosis of plants in the field of process and manufacturing industry, with solutions oriented to the implementation on industrial control and automation platforms (PLC, Motion Controllers, Fieldbuses, distributed sensors/actuators, Industrial Internet of Things - IIoT). 
  • Condition monitoring and predictive maintenance of automatic machines; particular attention is paid to continuous learning issues and to mixed computing platforms, taking advantage of both edge and cloud solutions (in collaboration with Prof. Roberto Diversi and Ing. Matteo Barbieri).  
  • Thermal modelling and optimized control for High Performance Computing (HPC), referring to multiple dimensional and time scales: from manycore processors to supercomputing facilities (in collaboration with Prof. Luca Benini, Ing. Andrea Bartolini and their research group).   

ERC Fields 

  • PE7_1 - Control engineering 
  • PE7_3 - Simulation engineering and modelling 
  • PE7_4 - Systems engineering, sensorics, actorics, automation 
  • PE7_7 - Signal processing 

Scientific coordinator: Prof. Andrea Tilli 


Andrea Tilli

Associate Professor

PhD Students and Research Fellows

Matteo Barbieri

Research fellow

Teaching tutor

Alessandro Bosso

Research fellow

Teaching tutor

Luca Orciari

Research fellow

Davide Raggini

Research fellow

Elena Ruggiano

PhD Student

Teaching tutor

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