Control Networks

Networks are the skeletons of real-world complex systems. They are used to describe various real systems, ranging from biological to technological systems, made up of many simple yet richly interacting units. Analyzing the structural and dynamical properties of networks is fundamental to explain the emergence of complex phenomena and to guide the design of control algorithms for manipulating or optimizing the behavior of real systems. The research activities in this area span across the analysis and control of biological networks, the design of distributed control policies for networks of smart agents, such as wireless sensors and cameras, and the modeling of opinion dynamics in social networks. 

 

Homepage: http://automatica.dei.unipd.it/people/zampieri.html

 

People: Sandro Zampieri (contact person),  Giacomo Baggio, Ruggero Carli, Angelo Cenedese, Alessandro Chiuso, Ettore Fornasini, Luca Schenato, Gianluigi Pillonetto, Francesco Ticozzi, Maria Elena Valcher

 

 

 

The research focuses on the analysis of the main theoretical properties of this class of systems, with possible applications in the context of genetic regulation networks. Ongoing projects are the following:

  • Optimal control of BCNs
  • Series and parallel connections of BCNs;
  • Fault detection and identification for BCNs
  • Identification of BCNs modeling genetic regulatory networks.

Homepage: http://www.dei.unipd.it/~meme/MEV/Main.html

People: Maria Elena Valcher (contact person), Ettore Fornasini

The research focuses on:

  • Sparse camera networks: Pan-Tilt-Zoom cameras and fixed cameras cooperate in videosurveillance distributed networks to perform tasks of area patrolling, event detection and event tracking. The systems are autonomic: cameras are smart agents able to coordinate to maximize surveillance performance, manage complex tasks, accommodate for camera losses (self-healing).
  • Dense camera networks: 3D reconstruction in motion capture systems shows critical issues when scaling with the number of cameras or the complexity of the scene. In this context a distributed approach is proposed to solve the multicamera reconstruction problem in large scale motion capture systems.

Ongoing specific research topics regard:

  • Network modeling and distributed calibration
  • Coordinated patrolling and tracking
  • Distributed reconstruction and optimal camera selection

Homepage: http://automatica.dei.unipd.it/research/camera-networks.html

People: Angelo Cenedese (contact person), Ruggero Carli, Luca Schenato

The research focuses on networked control systems which are systems composed of physically distributed smart agents that can sense the environment, act on it, and communicate with one other through a communication network to achieve a common goal. The challenges reside in the design of control systems that are robust to communication constraints like bandwidth, random delay and packet loss, to computational constraints due to the large amount of data to be processed or to the distributed nature of the sensing and control, to real-time implementation on limited resources devices, an to complexity to the large number of possibly unreliable agents involved. Ongoing specific reseach topics are:

  • Asynchronous consensus algorithms
  • Distributed convex optimization
  • Area-based asynchronous estimation
  • Clock synchronization in wireless sensor networks
  • Distributed algorithms robust to unreliable communication
  • Distributed blind sensor calibration
  • Control and estimation subject to random delay, packet loss and quantization

Homepage: http://automatica.dei.unipd.it/research/networked-control-systems.html

People: Luca Schenato (contact person), Ruggero Carli, Alessandro Chiuso, Angelo Cenedese, Gianluigi Pillonetto, Francesco Ticozzi, Sandro Zampieri