Model Predictive Control for Adaptable Space Applications

1 Research Project Fellow position
(Deadline August 20th, 2012 12:00 )
Automatic Control, Guidance Navigation and Control, Aerospace Control System, Model Predictive Control
Develop model predictive control (MPC) algorithms that are suitable for space applications and tailored to embedded applications on target multiprocessor systems, using rigorous auto-coding generation procedures. The MPC controllers should perform guidance, navigation and control (GNC) tasks. Perform trade-off studies between the MPC potentials and limitations taking into account processor implementation of on-line constrained optimization problems in the view of computational requirements. Demonstrate the effectiveness of the study on a set of relevant application problems in GNC of aerospace systems and on a flight demonstration based on industrial test-benches.
Formal requirements
You must currently be eligible for and enrolled in an Italian Ph.D. Program; excellent knowledge of English, both written and spoken.
Specific requirements
Possession of an undergraduate degree in engineering is preferable. The candidate should have a strong background in model predictive control of aerospace systems, such as unmanned aerial vehicles (UAVs), with skills in theoretical aspects, algorithms, in the MATLAB/Simulink environment for simulating MPC control of UAVs and in the hardware (mechanics, electronics, and software) constituting real flying prototypes.
"Model Predictive Control for Adaptable Space Applications" in collaboration with ESA - European Space Agency
Gross amount
€13.638 gross/year
36 months
Job Research Area: 
Job Research Unit: 
Full call
Second meeting of the Selection Committee
August 28th 2012
Preliminary shortlist
Preliminary shortlist
Final ranking
Final ranking


Apply ONLINE only.
Before starting prepare the application attachments and information as listed below.


  • Personal info and contact info (compulsory)
  • Number of your Identity Document (Passport or Identity Card) (compulsory)
  • University degree and ongoing PhD (compulsory)


  • Your CV in English (compulsory)