Prof. Girish Nair
Department of Electrical & Electronic Engineering
University of Melbourne, Australia
Tuesday 2018-03-13 16:00
IST-Seminar-Room 2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen
Set-membership filtering aims to determine the set of feasible states when the dynamics and measurements of a system are corrupted by bounded noise having unknown statistics. In this talk, it is explained how randomly generated particles can be used to approximate the feasible state set. The theory of random closed sets in continuous spaces is then used to prove stochastic, set-theoretic convergence as the number of particles increases. Two novel modifications are proposed, which generate random samples that are more evenly distributed over the feasible state set compared to the naive application of a particle filter. Simulation results show the superior performance of the proposed modifications (joint work with Dr. Pei Hua Leong)
Girish Nair was born in Malaysia and is a professor and ARC Future Fellow in the Department of Electrical and Electronic Engineering, University of Melbourne, Australia. He has previously held visiting positions at Uni. Padova, Italy, Boston Uni., USA, and ETH Zurich, Switzerland. He has received several prizes, including the IEEE CSS Axelby Outstanding Paper Award in 2014, a SIAM Outstanding Paper Prize in 2006, and the Best Theory Paper Prize at the UKACC Int. Conf. Control, Cambridge Uni., 2000. His interests are in networked control and information theory, and he is a Fellow of the IEEE.