Zoek medewerkers/organisaties dr.ir. C Sun PhD MSc
Naam
Naamdr.ir. C Sun PhD MSc
RoepnaamCongcong
Emailcongcong.sun@wur.nl

Werk
Omschrijvingdr.ir.
OrganisatieDepartement Plantenwetenschappen
OrganisatieeenheidAgrarische Bedrijfstechnologie
Telefoon+31 317 480 447
Mobiel+31 6 18869125
Telefoon secretariaat+31 317 482 980
Telefoon 2
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BezoekadresDroevendaalsesteeg 1
6708PB, WAGENINGEN
Gebouw/Kamer107/W3.Aa.043
Postadres
Bodenummer108
Reguliere werkdagen
Ma Di Wo Do Vr
Ochtend
Middag

Biografie

Congcong SUN is an engineer of computer science and control system. She has received her doctorate of Automatic Control from Technical University of Catalunya (UPC) in 2015. Since 2016, she worked as a postdoc researcher in the Institute of Robotic Industrial (IRI, UPC-CSIC). Since 2021/05, she has been working as an Assistant Professor in the Farm Technology Group of Wageninge University. Her research interests include: 1) Self-learning control of autonomous agricultural production systems for food safety, resource sustainability and pollution mitigation; 2) Planning, learning and control of Multi-agent agricultural robotic systems; 3) Integrated control and management of Water-Energy-Food nexus towards global efficiency and sustainability.


Expertiseprofiel
Expertise
Sociale media
  Congcong Sun op Google Scholar Citations
  Congcong Sun op Linkedin
  Congcong Sun op ResearchGate

Publicaties
Kernpublicaties

Projecten

DurableCASE: Durable Cooperative Agrobotics Systems Engineering

DurableCASE is a collaboration to develop solutions for collaborative robotic vehicles in the agricultural sector. DurableCASE stands for Durable Cooperative Agrobotics Systems Engineering: sustainable solutions for collaborative robots in the agricultural sector. 

The use of robots as a replacement for labor in this sector is increasingly becoming a necessity due to a lack of manpower. The perspective offers many possibilities, for example in the field of sustainability. Multiple compact robots can take over the tasks of one large machine. That saves soil compaction. It also provides greater operational reliability: if one robot fails, other robots can take over tasks. The robots have to work well together. 


DurableCASE develops solutions for communication between collaborating robots. The goal: robust cooperativity, where robust stands for safe, secure & performant. In other words, safe, secure and with optimum performance, under all circumstances. For robotics, there is a lot available in the rich ecosystem of ROS (Robot Operating System). DurableCASE makes grateful use of this. 

Data-driven modelling and control approach for discrete-time descriptor systems

Water/energy networks, aircraft, robot manipulators and unmanned aerial vehicles among others should be represented by differential/algebraic equations that can be formalized using the descriptor systems approach. On the other hand, thanks to the development of sensing and communication techniques, large amounts of data are available which lead the development of advanced data-based systems identification and automatic control approaches. This work is aimed to propose advanced modelling and real-time control approaches to improve performance of descriptor systems based on the most successful methodologies in the field of data science. The following specific tasks are expected to be fulfilled:
1. Data-driven methodologies based on regularization approaches, pattern recognition and kernel methods will be studied to enable more precise state estimation and dynamic prediction algorithms.
2. New real-time optimization methods and tools to take advantage of data information will be developed to ensure efficiency, stability and security of descriptor systems.
3. Real pilots will be used as case studies to demonstrate the proposed approaches.

Digital Twin: Realizing Resilient Operation of Critical Infrastructures (TWINs)

This project will focus on the most successful real-time supervision techniques in the field of data science and machine learning, based on a digital twin model, to realize resilient operation of critical infrastructure for early detection of faults or attacks, as well as for service reconfiguration after the detected event.


Onderwijs

2019-2020    Postgraduate in Data Science and Big Data, University of Barcelona, Spain

2011-2015    Ph.D. in Automation, Robotics and Vision, Institute of Robotic Industrial (IRI, UPC-CSIC), Spain   

2008-2011    M.Sc. in System Engineering, Tongji University, Shanghai, China

2004-2008    B.Sc. in Computer Science, Nanjing Audit University, Nanjing, China

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