A. Jokic

Pietro Kristović, Andrej Jokić, Mircea Lazar

In this paper we propose dynamic output-feedback controller synthesis methods for discrete-time linear time-invariant systems. The synthesis goal is to achieve dissipativity with respect to a given quadratic supply rate or a given $H_2$ performance level. It is assumed that the model of system dynamics is unknown, expect for the disturbance term. Instead, we have a recorded trajectory of the control input and the state, which can be corrupted by an unknown but bounded disturbance. The state data is used only for the purpose of controller synthesis, while the designed controller is output feedback controller, i.e., the full state is not used for control in real time. The presented synthesis method is formulated in terms of linear matrix inequalities parametrized by a scalar variable. Within the considered setting, the synthesis procedure is non-conservative.

Andrej Jokic, Nikola Vukovic

License plate recognition is the key component to many automatic traffic control systems. It enables the automatic identification of vehicles in many applications. Such systems must be able to identify vehicles from images taken in various conditions including low light, rain, snow, etc. In order to reduce the complexity and cost of the hardware required for such devices, the algorithm should be as efficient as possible. This paper proposes a license plate recognition system which uses a new approach based on compressive sensing techniques for dimensionality reduction and feature extraction. Dimensionality reduction will enable precise classification with less training data while demanding less computational power. Based on the extracted features, character recognition and classification is done by a Support Vector Machine classifier.