Control systems, automation and robotics


Advanced control technologies and algorithms have transformed the way we design and operate industrial, automotive, and robotic systems. These technologies enable precise control and automation of complex processes, leading to increased efficiency, productivity, and safety. In industrial applications, advanced control technologies and algorithms are used to optimize manufacturing processes, reduce waste, and improve quality. In automotive applications, these technologies enable advanced driver assistance systems and unmanned vehicles. In robotic applications, advanced control technologies and algorithms enable robots to perform intricate tasks with high precision. The development of these technologies requires expertise in multiple fields, including control theory, computer science, and electrical engineering.

On the theoretical/algorithmic side, this research area pursues methodological and applicative advances in modeling, identification, and control of dynamical systems, dealing also with complex and nonlinear systems, uncertain and complex systems, data-driven techniques (machine learning, reinforcement learning, physics-informed neural networks, interpretable/explainable AI), predictive models. Several applicative fields are considered, including: automotive systems, financial engineering, mobility-on-demand and smart transportations, manufacturing systems, biological and biomedical systems, soft sensors, logistics, aerospace.

On the practical implementation side, this activity investigates hardware platforms, embedded systems, sensor integration, and algorithms which are essential components of advanced automation systems and service robotic platforms. These technologies enable robots to sense and interact with their environment, make decisions based on data, and perform complex tasks autonomously. Embedded systems are at the heart of these technologies, providing the computing power and connectivity necessary for robots to operate. Sensor integration enables robots to perceive their environment and gather data about their surroundings. Algorithms then process this data and enable robots to make decisions and perform actions.


ERC sectors 

  • PE7_1 Control engineering
  • PE7_2 Electrical engineering: power components and/or systems
  • PE7_3 Simulation engineering and modelling
  • PE7_4 (Micro- and nano-) systems engineering
  • PE7_7 Signal processing
  • PE7_9 Man-machine interfaces
  • PE7_10 Robotics
  • PE6_1 Computer architecture, embedded systems, operating systems
  • PE8_1 Aerospace engineering


  • Modeling and Simulation
  • Control systems
  • Automation
  • Real-time
  • Robotics
  • Cooperative robotics
  • Embedded systems
  • ADAS
  • Sensor fusion
  • Human-machine interface