The research in optimization is focused on robust optimization, optimal control, robust control, model predictive control, signal processing and applications.

Robust Optimization

Within robust optimization work is carried out develop a software framework to unify much of the work which has been carried out in the robust control community. Many of the tricks of the trade can be automized, i.e. the resulting optimization problems for robust control can be derived in an automatic fashion. Much of this has been implemented in the modelling language YALMIP. It is our hope that support for robust optimization will have the same impact and success as YALMIP has had for conic optimization in general within the control community.

Optimal Control

Within optimal control work is carried out to generalize results to descriptor systems. Algorithms have been developed for solving the Hamilton-Jacobi equation without first converting the problem to state space form. These algorithms also make it possible to compute nonlinear controllability measures and to do model reduction.

Robust Control

Within robust control recent work is focused on reduced order robust controller design, model reduction, and robustness analysis. For robustness analysis efficient optimization algorithms for semidefinite programs related to the KYP lemma have been developed that significantly reduce the computational complexity.

Model Predictive control

Work on robust model predictive control and on model predictive control for hybrid systems is also an active research area. JL Within hybrid model predictive control a novel dual active set quaratic programming algorithm has been developed which show good performace in the branch and bound framework used for solving the mixed integer quadratic programmaing problems that have to be solved.

Multiuser Detection

Recently work has been carried out in deriving efficient algorithms for multiuser detection. Also here the key is to efficietly solve integer quadratic programs, which in this case is carried out using a cleaver pre-processing algorithm.

Clearance of Flight control Laws

Two projects on application of optimization to clearance of flight control laws are carried out. In this work the algorithms developed for robustness analysis are tested on large scale models of aircraft.