Giorgio.. D. Kwame Minde Kufoalor

Postdoctoral Research Fellow Department of Engineering Cybernetics
+47 73594391

Background and activities

I am currently working with the Autosea project team to develop an overall system architecture of a future navigation and control system with sensor fusion and collision avoidance (COLAV). Our main goal is to identify and specify interface requirements and dataflow between sensor fusion and collision avoidance modules, in order to achieve a reliable autonomous COLAV system for surface vehicles. 

My research focus in the Autosea project include

  • strategic and tactical collision avoidance algorithms,
  • system design specification for software and hardware modules needed to achieve a reliable COLAV system,
  • and extensive reliability, availability and maintainability (RAM) analysis for autonomous COLAV systems.

 My research interests are in the areas of

  • guidance, navigation and control of vehicles,
  • embedded model predictive control,
  • numerical optimal control and optimization,
  • power/energy management and automation systems,
  • and reconfigurable fault-tolerant control.

 

Scientific, academic and artistic work

A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database

Journal publications

Part of book/report

  • Binder, Benjamin Julian Tømte; Kufoalor, D. Kwame Minde; Johansen, Tor Arne. (2015) Scalability of QP solvers for embedded model predictive control applied to a subsea petroleum production system. 2015 IEEE Conference on Control Applications, CCA 2015.
  • Kufoalor, D. Kwame Minde; Binder, Benjamin Julian Tømte; Ferreau, Hans Joachim; Imsland, Lars Struen; Johansen, Tor Arne; Diehl, M. (2015) Automatic Deployment of Industrial Embedded Model Predictive Control Using qpOASES. Proceedings of the 14th European Control Conference 2015 (ECC 2015).

Report/dissertation

  • Kufoalor, D. Kwame Minde. (2016) High-performance Industrial Embedded Model Predictive Control. 2016. ISBN 978-82-326-1652-7.