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40 results on '"Djurovic, Zeljko"'

5. A New Approach to Signal-to-Noise Ratio Estimation in Adaptive Doppler–Kalman Filter for Radar Systems.

Author

Papic, Veljko and Djurovic, Zeljko

Subjects
*SIGNAL-to-noise ratio, *ADAPTIVE filters, *KALMAN filtering, *RADAR antennas, *RELATIVE velocity, *SIGNAL processing, *WHITE noise, *AMPLITUDE estimation
Abstract

Doppler frequency carries the information about the relative velocity of the object regarding the radar antenna. However, since the target maneuvers can be temporary with high intensity, Doppler frequency has to be estimated by using a window function in the frame of time-dependent Fourier transform. In order to minimize the estimation error, the window function width should be adaptive. The window length adaptation has been performed based on the estimates of target acceleration and signal-to-noise ratio (SNR). In this paper, we give focus on the SNR estimation and propose a new approach based on autoregressive method of spectral estimation, where in one step the amplitude of the sinusoidal signal and noise variance are estimated. The simulation results justify the advantage of the proposed approach in general applications of signal processing of one sinusoid in white noise environment. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Robust tracking of moving objects using thermal camera and speeded up robust features descriptor.

Author

Vlahović, Nataša and Djurovic, Zeljko

Subjects
*OBJECT tracking (Computer vision), *TRAFFIC cameras, *KALMAN filtering, *THERMOGRAPHY, *ARTIFICIAL satellite tracking, *NONLINEAR functions, *PERFORMANCE standards
Abstract

Summary: Robust methods based on nonlinear influence functions are often used to remove outliers from data. The article describes the design of an algorithm for tracking a moving object in a thermal image using a SURF descriptor and robust Kalman filter. However, given that the main shortfall of robust methods is reduced efficiency, tunable parameters of the robust influence function are used to achieve a balance between robustness and efficiency. The parameters adapt to the observed scene's current conditions, while their estimation is based on the calculated data outlier contamination factor. The outliers that contaminate the data are generally a result of various types of occlusions. The results show that the proposed solution achieves better performance than the standard Kalman filter or fixed‐parameter robust Kalman filter. [ABSTRACT FROM AUTHOR]

Published
2021
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18. Expert system for fault detection and isolation of coal-shortage in thermal power plants

Author

M. Djurovic Zeljko, R. Tadic Predrag, and M. Todorovic Veljko

Subjects
0209 industrial biotechnology, Engineering, Power station, business.industry, Thermal power station, 020206 networking & telecommunications, Control engineering, 02 engineering and technology, computer.software_genre, Fault (power engineering), 7. Clean energy, Fault detection and isolation, Automotive engineering, Expert system, 020901 industrial engineering & automation, Electricity generation, 0202 electrical engineering, electronic engineering, information engineering, Coal, business, computer, Block (data storage)
Abstract

A two layer fault detection and isolation (FDI) system for coal-shortage detection in thermal power plant coal supply unit has been proposed. If the amount of coal reaching the burners is not sufficient enough we are facing possibly hazardous working conditions and this situation is treated as fault and has to be detected as soon as possible. Layer one of a proposed system consists of two FDI algorithms running in parallel: FDI expert system and algorithm based on fixed size hypothesis testing strategy. Residuals generated by layer one are passed to layer two expert system for evaluation and final decision on whether a coal-shortage really occurred. Two layer FDI structure is used to generate more reliable and faster FDI. Proposed system is tested with data collected from coal supply unit of block A4 of "Nikola Tesla" power plant (Obrenovac, Serbia) and results are discussed in detail.

Published
2010

22. Consensus Based Overlapping Decentralized Fault Detection and Isolation

Author

Stankovic, Srdjan S., Ilic, Nemanja, Djurovic, Zeljko, Stankovic, Milos S., Johansson, Karl H., Stankovic, Srdjan S., Ilic, Nemanja, Djurovic, Zeljko, Stankovic, Milos S., and Johansson, Karl H.

Abstract

In this paper a new distributed fault detection and isolation (FDI) methodology is proposed in the form of a multi-agent network representing a combination of a consensus based FDI observer for residual generation and a consensus based decision making strategy for change detection, applicable in real time. The proposed observer is based on overlapping system decomposition and a combination between the local optimal stochastic FDI observers and a dynamic consensus strategy. It is shown how the proposed algorithm can generate residuals which provide, under general conditions concerning local models and the network topology, high efficiency, scalability and robustness. The proposed decision making strategy provides solutions for two particular cases: a) local detection for non-overlapping parts of the identified subsystems; b) a consensus based strategy for FDI in the overlapping parts.One selected example illustrates the applicability of the proposed methodology in practice., QC 20120202

Published
2010
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35. To robust identification of water steam-separator process in thermal power plants.

Author

Kvascev, Goran, Marjanovic, Aleksandra, Tadic, Predrag, and Djurovic, Zeljko

Abstract

One of the primary requirements for a high performance process control is a good quality and reliability of obtained measurements. In order to overcome the problem of sporadic high-intensity irregular measurements (outliers) presence, a robust process identification procedure must be used. The paper presents an application of an adaptive approach to robust parameter estimation of a linear dynamic discrete-time system, based on QQ-plot method together with robustified winsorization technique. The proposed procedure is implemented in a stemseparator system in thermal power plants. The comparison to the conventional RLS approach demonstrates the effectiveness of this method in the presence of impulse noise. [ABSTRACT FROM PUBLISHER]

Published
2012
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38. Simulation of air turbulence signal and its applications

Author

Djurovic, Zeljko, Miskovic, Ljubisa, and Kovacevic, Branko

Subjects
Physics::Fluid Dynamics, aerospace simulation, filtering theory, signal processing, Physics::Atmospheric and Oceanic Physics, spectral analysis, atmospheric turbulence
Abstract

The air turbulence signal is one of the most important disturbances that act during the flight of the aircraft, and therefore, the simulation of atmospheric turbulence is of considerable importance in the evaluation of an aircraft performance in real conditions. Passing a white stochastic sequence through the adequately designed linear filter, the obtained signal at its output will be with a power spectral density very close to the von Karman power spectral density model of air turbulence. The paper presents an analysis of the influence of the filter order and an optimization procedure for filter parameters tuning, in order to obtain a suitable approximation of the von Karman spectra.

39. Velocity tracking based on adaptive Doppler filters

Author

Papic, Veljko, Djurovic, Zeljko, Miskovic, Ljubisa, and Kovacevic, Branko

Subjects
adaptive filters, doppler radar, adaptive estimation, target tracking
Abstract

In order to obtain target velocity in radar systems we use Doppler filters. It is usual in such applications to use window functions with prespecified shape and length. For a good target velocity estimation, it is necessary to apply adaptive length window functions. The optimum length is primarily influenced by the target dynamics, expressed in its acceleration, and the signal to noise ratio of the obtained echo. In this paper, we have proposed a very simple and accurate procedure for an estimation of the target acceleration. We assumed signal to noise ratio to be constant. The efficiency of the procedure has been demonstrated through computer simulations.

40. Nonlinear system control using the MSEV approach

Author

Miskovic, Ljubisa, Djurovic, Zeljko, and Kovacevic, Branko

Subjects
random processes, self-tuning systems, nonlinear control, time-varying systems
Abstract

A class of modified state-space self-tuning controllers of the MSEV (minimum state error variance) type is considered in this article. A suitable chosen structure for the proposed controller provides for tracking the time-varying reference input, and makes it possible to apply this solution to nonlinear and nonstationary plants. Starting from the changes of innovations sequence statistics, an efficient load disturbance detector is also constructed, and the estimated disturbance amplitude is used to correct the control signal, in order to eliminate the influence of disturbances. The advantage in using the proposed algorithm for nonlinear systems control, in the presence of load disturbances and stochastic disturbances of unknown statistics, is demonstrated through simulation results.

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