The text below is a brief description of the topics given by professor Lars Imsland. Contact lars.imsland@itk.ntnu.no for further information.

1. Techniques for efficient covariance propagation in the Extended Kalman Filter, based on model reduction
   Even though the (recursive) EKF is considered an efficient algorithm for state estimation, it can still be computationally expensive for large/complex systems. The bulk of the complexity stems from the propagation of the state covariance matrix. In this task, the student will consider using techniques from model reduction to make the covariance propagation more efficient, while the full model still is used for state propagation.
2. Fault tolerant control (FTC) of offshore drilling process
   In offshore drilling, secure control of bottomhole pressure is important, also in case of equipment failure. The task of this project is to develop fault tolerant control algorithms for some aspects of the drilling process.