Maja Atanasijevic-Kunc

Learn More
In this paper an approach to a study of multivariable system control is presented, where special attention is devoted to the implemented remote experiment. It has been realized through an e-learning environment, based on the ECHO , Matlab, PHP software and a MySQL database. The e-management system ECHO has been developed at the Faculty of Electrical(More)
Rising demand for electrical power and environmental awareness has triggered new types of electrical power producers like solar and wind power plants. They cause a problem in electrical power system because of their stochastic nature of energy production. Smart grid technology offers a solution to these problems. In this paper a smart grid solution made for(More)
The paper deals with some important aspects of continuous systems modelling education. Namely the traditional approach is based on block oriented schemes in which causal relations play an important role. However this causality is artificially generated in order to fulfil appropriate conditions for simulation on conventional sequential computers. Fortunately(More)
The paper deals with a systematic approach to the control system design with a final goal to efficiently control some living conditions in a test chamber. The mathematical model was implemented in MATLAB Simulink environment. The structure is modular, the robust numerical algorithms give accurate results and fast simulation runs. The developed simulator(More)
In this paper a new scheduling algorithm is presented that enables fast calculation times with a combination of neural network and local optimization. Properly learned neural network is used to calculate schedule results that can be used as initial conditions for local optimization method. If scheduling results from neural network are located relatively(More)
The paper presents a new energy scheduling approach enabling fast calculation times with a combination of the neuron network and local optimization. A learned neuron network is used to calculate the energy scheduling results to be used as initial conditions for a local energy scheduling optimization method. When the scheduling results from a neuron network(More)