Input design and data-driven approaches based on convex optimization for fault diagnosis in linear systems

The complexity of automated systems has grown considerably during the past decades. This convolutes the observation of possible faults in these systems. If not being revealed timely, such faults can lead to catastrophic failures. As a result, there is a continuous interest in sophisticated fault diagnosis techniques. Since it is generally...

Graph filter design using sum-of-squares representation

Graph filters are an essential part of signal processing on graphs enabling one to modify the spectral content of the graph signals. This paper proposes a graph filter optimization method with an exact control of the ripple on the passband and the stopband of the filter. The proposed filter design method is based on the sum-of-squares...

Spatio-temporal field estimation using kriged kalman filter (KKF) with sparsity-enforcing sensor placement

We propose a sensor placement method for spatio-temporal field estimation based on a kriged Kalman filter (KKF) using a network of static or mobile sensors. The developed framework dynamically designs the optimal constellation to place the sensors. We combine the estimation error (for the stationary as well as non-stationary component of the...