Branko Kovacevic - Academia.edu (original) (raw)

Papers by Branko Kovacevic

Svrha ovog rada je da odgovori na nekoliko pitanja: U kojoj su mjeri razne teorije poduzeca utjec... more Svrha ovog rada je da odgovori na nekoliko pitanja: U kojoj su mjeri razne teorije poduzeca utjecale na nastanak suvremenih pristupa organizaciji? Jesu li razne teorije poduzeca supstituti ili komplementi? Sto je, uz imanentni teorijski razvoj utjecalo na nastanak novih pristupa? To je utjecalo i na raspored teksta: najprije se daje pregled postojecih teorija, zatim stakeholderski pristup i koncept virtualne organizacije poduzeca. Na kraju se daju nalazi istraživanja i zakljucak. U generalnom se zakljucku obrazlaže povezanost razlicitih teorija i ukorijenjenost novih pristupa u povijesnim teorijama poduzeca. No, uz to se navode i promijenjene povijesne okolnosti (globalizacija, nove tehnologije, neizvjesnost i nestabilnost konkurentskog okruženja) koje su također utjecale na nastanak novih pristupa. Ukazuje se na sve vecu dominaciju raznih teorija sposobnosti (resursnih teorija) u kojima je naglasak na procesu ucenja, prilagodbi i predviđanju promjena u okruženju.

Control and Intelligent …, 2000

A class of modified state-space self-tuning controllers of the MSEV (minimum state error variance... more A class of modified state-space self-tuning controllers of the MSEV (minimum state error variance) type is has been 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.

EURASIP Journal on Advances in Signal Processing, 2016

In this paper, a new adaptive robustified filter algorithm of recursive weighted least squares wi... more In this paper, a new adaptive robustified filter algorithm of recursive weighted least squares with combined scale and variable forgetting factors for time-varying parameters estimation in non-stationary and impulsive noise environments has been proposed. To reduce the effect of impulsive noise, whether this situation is stationary or not, the proposed adaptive robustified approach extends the concept of approximate maximum likelihood robust estimation, the so-called M robust estimation, to the estimation of both filter parameters and noise variance simultaneously. The application of variable forgetting factor, calculated adaptively with respect to the robustified prediction error criterion, provides the estimation of time-varying filter parameters under a stochastic environment with possible impulsive noise. The feasibility of the proposed approach is analysed in a system identification scenario using finite impulse response (FIR) filter applications.

EUROCON 2005 - The International Conference on "Computer as a Tool", 2005

New algorithm for estimation of parameters of communication channel in the circumstances of exist... more New algorithm for estimation of parameters of communication channel in the circumstances of existence of intensive impulse noise within measurement sequence is proposed in this paper. Proceeding from the theory of robust estimation, a simple, adaptive, practically applicable algorithm is derived that in the circumstances of contaminated normal distribution of measurement noise demonstrates high level of efficiency. QQ-plot technique is

International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service, 2001

A new practical solution for target tracking in air space with passive infrared (IR) sensors is p... more A new practical solution for target tracking in air space with passive infrared (IR) sensors is presented. A suggested filter is based on an interacting multiple models (IMM) algorithm and angle-only measurements from passive missile sensors using point IR detectors

Facta universitatis - series: Electronics and Energetics, 2003

Comparison of several target tracking algorithms is presented. Namely discrete noise level adjust... more Comparison of several target tracking algorithms is presented. Namely discrete noise level adjustment (DNLA), variable state dimension (VSD) and interacting multiple model (IMM) algorithms are discussed. Target trajectory, target models, filtering algorithms and simulation results are given. The cumulative estimation error criterion is used in order to compare the algorithms.

Speech Communication, 2002

International Journal of Systems Science, 2002

A class of modi®ed state space self-tuning controllers of the minimum state error variance type w... more A class of modi®ed state space self-tuning controllers of the minimum state error variance type was considered. A suitable chosen structure of the proposed controller allows the tracking of a time-varying reference input and makes a possibility of applying this solution to nonlinear and non-stationar y plants. The advantage in using the proposed algorithm for nonlinear systems' control is demonstrated through its application to aircraft control around a prespeci®ed reference trajectory in the presence of characteristic disturbances. The results show that the proposed controller has good tracking performance and possesses rather good immunity towards disturbances.

IET Signal Processing, 2009

A new solution for target tracking in air space with two infrared (IR) sensors is presented. The ... more A new solution for target tracking in air space with two infrared (IR) sensors is presented. The principle of triangulation is used as a basic method for range estimation. However, when the target directions are nearly collinear relative to the baseline, this method produces unacceptable results. The problem is solved by introducing the ratio of IR energy adsorbed at the end of a baseline in a measurement vector within the extended Kalman filter type target state estimator. Also, a recursive estimator for the extinction coefficient that describes the influence of the atmosphere is designed. This combination results in a new adaptive structure for simultaneous estimation of target kinematic states and atmospheric parameters. Such a structure performs much better than the standard triangulation method, yielding acceptable results even in the case where target directions are close to the baseline. Simulation and experimental results demonstrate the feasibility and limitations of the proposed approach.

IET Control Theory & Applications, 2011

A new adaptive algorithm for the robust estimation of parameters of linear dynamic discrete-time ... more A new adaptive algorithm for the robust estimation of parameters of linear dynamic discrete-time systems in the presence of non-Gaussian impulsive noise within a measurement sequence is proposed in this study. Starting from the theory of robust estimation, a simple, adaptive, practically applicable robust approximate maximum likelihood algorithm is derived that, in the cases of contaminated normal distribution of measurement noise, demonstrates a high level of efficiency. The QQplot technique, combined with data cleaning based on the robustified winsorisation technique, is used as a framework for the classification of sorted data into the class of regular normally distributed data and the class of irregular data belonging to the contaminating distribution with a variance that is much greater than nominal. The link between the QQ-plot technique and a specific linear regression is established, so that the estimation of statistical parameters of the contaminated measurement distribution is performed using the least-squares technique. Then, the suboptimal maximum likelihood criterion is defined, and the system parameter estimation problem is solved robustly, using the proposed recursive robust parameter estimation scheme. Simulation results illustrate the discussion and show the efficiency of the proposed adaptive recursive parameter estimation algorithm in the presence of glint spikes or outliers.

IEE Proceedings - Vision, Image, and Signal Processing, 2001

The recursive algorithms of stochastic gradient type for estimating the parameters of linear disc... more The recursive algorithms of stochastic gradient type for estimating the parameters of linear discrete-time systems in the presence of disturbance uncertainty has been considered in the paper. Problems related to the construction of min-max optimal recursive algorithms are demonstrated. In addition, the robustness of the proposed algorithms has been addressed. Since the min-max optimal solution cannot be achieved in practice, a simple procedure for constructing a practically applicable robustified recursive algorithm based on a suitable nonlinear transformation of the prediction error and convenient approximations is suggested. The convergence of the robustified recursive algorithm is established theoretically using the martingale theory.

IFAC Proceedings Volumes, 1984

In this paper the problem of robust real-time identification of linear discrete-tlme multivariabl... more In this paper the problem of robust real-time identification of linear discrete-tlme multivariable systems is considered. Three methodol og ically different approaches t o the synthesis of such algorithms are presented. They are based on the generalized least-squares criterion, the optimal one-step estimation and the optimization of the stochastic approximation algorithm with respect to its weighting matri x. Properties of the derived alg orithms in the presence of approximately normal disturbances are analysed by ~onte Carlo simulations. The obtained results indicate the mos t suitable algori• thms for the application in the engineering practice.

Tehnicki vjesnik - Technical Gazette, 2015

Original scientific paper A new class of adaptive robust predictors has been considered in the pa... more Original scientific paper A new class of adaptive robust predictors has been considered in the paper. First an optimal predictor is developed, based on the minimization of a generalized mean square prediction error criterion. Starting from the obtained result, an adaptive robust predictor is synthesized through minimization of a modified criterion in which a suitably chosen non-linear function of the prediction error is introduced instead of the quadratic one. Unknown parameters of the predictor are estimated at each step by applying a recursive algorithm of stochastic gradient type. The convergence of the proposed adaptive robustified prediction algorithm is established theoretically using the Martingale theory. It has been shown that the proposed adaptive robust prediction algorithm converges to the optimal systems output prediction. The feasibility of the proposed approach is demonstrated by solving a practical problem of designing a robust version of adaptive minimum variance controller.

Scientific Technical Review, 2016

The radar tracking applications perform single and multiple object detections from noise-corrupte... more The radar tracking applications perform single and multiple object detections from noise-corrupted signal. These detections are used as measurements for target tracking. Tracking in cluttered environments requires false track discrimination and data association. However, data association for tracking closely located multiple targets in heavy clutter is prohibitive due to the excessive computational requirement. This results from exponential growth of mutually exclusive and exhaustive feasible joint events for track-to-measurement assignment. Specifically, our approach treats possible detections of targets followed by other tracks as additional clutter measurements. It starts by approximating the a priori probabilities of measurement origin. These probabilities are then used to modify the clutter spatial density at the location of the measurements. The probability of target existence is used to discriminate the false tracks. The extended simulations showed the effectiveness of this approach in two different multi-target tracking scenarios.

IEEE Transactions on Control Systems Technology, 2017

High demands for increasing robustness, safety, and efficiency in thermal power plants are the ma... more High demands for increasing robustness, safety, and efficiency in thermal power plants are the main motivation behind ongoing attempts to optimize combustion. This paper presents a study of modeling and control of the combustion process in a tangentially fired pulverized-coal boiler. It proposes an approach to flame geometry and position control by means of reallocation of firing. Such control ensures flame focus maintenance away from the walls of the boiler, and thus prevents many unwanted by-products of combustion. In addition, uniform heat dissipation over mills enhances the energy efficiency and reliability of the boiler. First, experimental data obtained from the 350-MW boiler of the Nikola Tesla power plant, Serbia, are analyzed in detail. This results in a model identification procedure using an adaptive parameter estimation method. Second, constrained multivariate extremum seeking (ES) is proposed in this paper, to optimally tune boiler operation in order to maintain the desired flame configuration in the furnace. Finally, the effectiveness of the ES adaptive controller in the presence of disturbances is demonstrated through simulations performed on the experimentally identified model of the boiler.

Advances in Intelligent Systems and Computing, 2016

The purpose of this article is to provide an overview of soft computing applications in actuarial... more The purpose of this article is to provide an overview of soft computing applications in actuarial science. Soft computing (SC) refers to modes of computing in which precision is traded for tractability, robustness and ease of implementation. For the most part, SC encompasses the technologies of fuzzy logic, genetic algorithms, and neural networks, and it has emerged as an effective tool for dealing with control, modeling, and decision problems in complex systems. The paper ends with a general comment on the study. arc35_11_01a