Associate Professor

Zoran Tomljanović

Vice-Dean for Teaching and Students
ztomljan@mathos.hr
+385-31-224-827
18 (ground floor)
School of Applied Mathematics and Informatics

Josip Juraj Strossmayer University of Osijek

Research Interests

Numerical linear algebra
Damping optimization in mechanical systems
Control theory
Matrix equations

Degrees

PhD in Mathematics, Department of Mathematics, University of Zagreb, May 2011,
MSc in Mathematics, Department of Mathematics, University of Zagreb, Croatia, December 2005,
1997-2001 Mathematical Gymnasium at high school in Našice

Publications

Journal Publications

  1. Z. Tomljanović, $H_{\infty}$ Analysis of Cooperative Multi-Agent Systems by Adaptive Interpolation, Applications of Mathematics 70/3 (2025), 367-386
    We consider a projection-based model reduction approach to computing the maximal impact, one agent or a group of agents has on the cooperative system. As a cri- terion for measuring the agent-team impact on multi-agent systems, we use the H∞ norm, and output synchronization is taken as the underlying cooperative control scheme. We investigate a projection-based model reduction approach that allows efficient H∞ norm calculation. The convergence of this approach depends on initial interpolation points, so we present approaches to their determination. Since the analysis of multi-agent systems is important from different perspectives, several comparisons are presented in the section on numerical experiments. A graph Laplacian matrix of an inter-agent interaction graph is a foundational element in modeling and analyzing multi-agent systems. We consider various graph topology matrices, system parameters, and excitations of different agents. Different strategies for selecting initial interpolation points are also compared with baseline approaches for calculating the H∞ norm.
  2. D. Palitta, Z. Tomljanović, I. Nakić, J. Saak, Efficient solution of sequences of parametrized Lyapunov equations with applications, Numerical Linear Algebra with Applications 32/1 (2025), 1-21
    Sequences of parametrized Lyapunov equations can be encountered in many application settings. Moreover, solutions of such equations are often intermediate steps of an overall procedure whose main goal is the computation of $trace(EX)$, where $X$ denotes the solution of a Lyapunov equation and $E$ is a given matrix. We are interested in addressing problems where the parameter dependency of the coefficient matrix is encoded as a low-rank modification to a seed, fixed matrix. We propose two novel numerical procedures that fully exploit such a common structure. The first one builds upon the Sherman-Morrison-Woodbury (SMW) formula and recycling Krylov techniques, and it is well-suited for small dimensional problems as it makes use of dense numerical linear algebra tools. The second algorithm can instead address large-scale problems by relying on state-of-the-art projection techniques based on the extended Krylov subspace. We test the new algorithms on several problems arising in the study of damped vibrational systems and the analyses of output synchronization problems for multi-agent systems. Our results show that the algorithms we propose are superior to state-of-the-art techniques as they are able to remarkably speed up the computation of accurate solutions.
  3. K. Sabo, R. Scitovski, Š. Ungar, Z. Tomljanović, A method for searching for a globally optimal k-partition of higher-dimensional datasets, Journal of Global Optimization 89/ (2024), 633-653
    The problem with finding a globally optimal k-partition of a set A is a very intricate optimization problem for which in general, except in the case of one-dimensional data, i.e., for data with one feature (A\subset\R), there is no method to solve. Only in the one-dimensional case there exist efficient methods that are based on the fact that the search for a globally optimal partition is equivalent to solving a global optimization problem for a symmetric Lipschitz-continuous function using the global optimization algorithm DIRECT. In the present paper, we propose a method for finding a globally optimal k-partition in the general case (A\subset \R^n, n\geq 1), generalizing an idea for solving the Lipschitz global optimization for symmetric functions. To do this, we propose a method that combines a global optimization algorithm with linear constraints and the k-means algorithm. The first of these two algorithms is used only to find a good initial approximation for the $k$-means algorithm. The method was tested on a number of artificial datasets and on several examples from the UCI Machine Learning Repository, and an application in spectral clustering for linearly non-separable datasets is also demonstrated. Our proposed method proved to be very efficient.
  4. N. Truhar, Z. Tomljanović, M. Ugrica, M. Karow, Efficient approximation of novel residual bounds for a parameter dependent quadratic eigenvalue problem, Numerical Algebra, Control and Optimization (2024), 1-9
    This paper contributes to the perturbation theory for parameter dependent quadratic eigenvalue problems (PQEP). Specifically, we derive an approximate perturbation bound between individual unperturbed and perturbed eigenvectors for PQEP. We also derive a modified but practically more useful eigenvector perturbation bound using the Taylor expansion of eigenvalue functions. The quality of the obtained bounds is illustrated by numerical examples.
  5. I. Nakić, M. Pilj Vidaković, Z. Tomljanović, Finite time horizon mixed control of vibrational systems, SIAM Journal on Scientific Computing 46/3 (2024), 280-305
    We consider a vibrational system control problem over a finite time horizon. The performance measure of the system is taken to be $p$-mixed $H_2$ norm which generalizes the standard $H_2$ norm. We present an algorithm for efficient calculation of this norm in the case when the system is parameter dependent and the number of inputs or outputs of the system is significantly smaller than the order of the system. Our approach is based on a novel procedure which is not based on solving Lyapunov equations and which takes into account the structure of the system. We use a characterization of the $H_2$ norm given in terms of integrals which we solve using adaptive quadrature rules. This enables us to use recycling strategies as well as parallelization. The efficiency of the new algorithm allows for an analysis of the influence of various system parameters and different finite time horizons on the value of the $p$-mixed $H_2$ norm. We illustrate our approach by numerical examples concerning an $n$-mass oscillator with one damper.


Projects

  • Optimization of parameter-dependent systems with applications — scientific project (IP-2025-02-4862, OPT-PEDESTAL). This project has been fully supported by Croatian Science Foundation for the period 01.12.2025. – 30.11.2028. (principal investigator)
  • Accelerated solution of optimal damping problems, — scientific project; supported by the DAAD for period 2021–2022 (principal investigator together with Jens Saak); cooperation with Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
  • Vibration Reduction in Mechanical Systems — scientific project (IP-2019-04-6774, VIMS). This project has been fully supported by Croatian Science Foundation for the period 01.01.2020.–31.12.2023. (principal investigator)
  • Control of Dynamical Systems — scientific project (IP-2016-06-2468, ConDyS). This project has been fully supported by Croatian Science Foundation for the period 01.03.2017.–28.02.2021. (investigator)
  • Robustness optimization of damped mechanical systems, — scientific project; supported by the DAAD for period 2017–2018 (principal investigator together with Matthias Voigt); cooperation with TU Berlin, Germany
  • Optimization of parameter dependent mechanical systems  — scientific project (IP-2014-09-9540; OptPDMechSys). This project has been fully supported by Croatian Science Foundation for the period 01.07.2015.–30.06.2019. (investigator)
  • Damping optimization in mechanical systems excited with external force — scientific project; supported by the J. J. Strossmayer University of Osijek for period 2015 (principal investigator)
  • Mixed Integer Nonlinear Programming (MINLP) for damper optimization — scientific project; supported by the DAAD for period 2015–2016 (investigator); cooperation with Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
  • European Model Reduction Network (EU-MORNET). Funded by: COST (European Cooperation in Science and Technology) (investigator).
  • Optimization of semi-active damping in vibrational systems — scientific project; supported by the J. J. Strossmayer University of Osijek for period 2014 (principal investigator); cooperation with Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
  • Optimal Damping of Vibrating Systems — scientific project; supported by the DAAD for period 2013–2014 (investigator)
  • Passive control of mechanical models — scientific project No.235-2352818-1042 of the Croatian Ministry of Science, Education and Sports for period 2007.– (investigator)
  • Optimization algorithms for determination of optimal damping in mechanical systems — scientific project; supported by the Croatian Science Foundation for period 2008–2009 (principal investigator)

Professional Activities

Professional Societiey Membership

  • GAMM Activity Group Applied and Numerical Linear Algebra, GAMM ANLA
  • Croatian Mathematical Society, HMD
  • Croatian Operational Research Society, CRORS
  • Society for Industrial and Applied Mathematics, SIAM
  • Croatian association for applied and industrial mathematics CRO-MATH-IN

 

Committee Memberships and Organization

  • UPCOMING: Co-organizer of the 5th Workshop on Optimal Control of Dynamical Systems and Applications, 10-13 May 2027 in Mon Perin resort in Istria, Croatia: webpage
  • Co-organizer of the 4th Workshop on Optimal Control of Dynamical Systems and Applications, 26-28 Feb 2025 in Villany, Hungary: webpage
  • Co-organizer of the 8th Croatian Mathematical Congress in Osijek , to be held on July 2 – 5, 2024, at the School of Applied Mathematics and Informatics in Osijek.
  • Co-organizer of the Winter School on Model Reduction for Optimization and Control that will be held on 19 – 23 February 2024 in Dubrovnik, Croatia: webpage
  • Co-organizer of the 3rd Workshop on Optimal Control of Dynamical Systems and Applications, 28-31 March 2022 at Department of Mathematics, J. J. Strossmayer University of Osijek: webpage
  • Co-organizer of the Workshop on Optimal Control of Dynamical Systems and Applications, 5-6 November 2020 at Department of Mathematics, J. J. Strossmayer University of Osijek: webpage
  • Co-organizer of the 10th Conference on Applied Mathematics and Scientific Computing 14-18 September 2020, Brijuni, Croatia. In 2020, we have a special section on optimal control of dynamical systems and applications, coorganized with the Department of Mathematics, University of Osijek, webpage
  • Co-organizer of International Workshop on Optimal Control of Dynamical Systems and Applications, 20-22 June 2018 at Department of Mathematics, J. J. Strossmayer University of Osijek,  webpage
  • Co-organizer of Workshop on Model Reduction Methods and Optimization, 20-21 September 2016, in Opatija, Croatia, webpage
  • Co-organizer of The third International School on Model Reduction for Dynamical Control Systems, 5 – 10 October 2015, in Dubrovnik, Croatia, webpage
  • Co-organizer of the DAAD International School on Linear Optimal Control of Dynamic Systems, 23 – 28 September 2013, Osijek, webpage
  • Co-organizer of the Summer School on Numerical Linear Algebra for Dynamical and High-Dimensional Problems, October 10-15, 2011, Trogir, Croatia, webpage

Teaching

Konzultacije (Office Hours):

Termini sljedećih konzultacija (ured 18 u prizemlju):

  • srijedom u 9:00 sati

Teme diplomskih i završnih radova:

U nastavku se nalaze nazivi tema i kratki opis, a više informacija studenti mogu dobiti na konzultacijama. Mole se zaniteresirani studenti da se jave ukoliko su zainteresirani za neku od tema.

  • Numeričko rješavanje običnih diferencijalnih jednadžbi
    – Većina diferencijalnih jednadžbi koje opisuju realne pojave nema rješenje u zatvorenoj formi, pa se do rješenja dolazi numerički. U ovom diplomskom radu obradit ćemo jednokoračne metode za početni problem: eksplicitnu i implicitnu Eulerovu metodu te metode Runge–Kutta, s naglaskom na klasičnu metodu četvrtog reda. Za svaku ćemo metodu izvesti lokalnu pogrešku diskretizacije, odrediti red konvergencije i ispitati područje apsolutne stabilnosti, čime se objašnjava zašto eksplicitne metode zakazuju na krutim problemima. Metode ćemo implementirati u MATLAB-u (ili C-u) i usporediti ih na primjerima različite naravi — harmonijskom oscilatoru, Van der Polovu oscilatoru i Lotka–Volterrinu modelu. Red konvergencije potvrdit ćemo logaritamskim dijagramom pogreške u ovisnosti o koraku, a efikasnost mjeriti brojem evaluacija desne strane potrebnih za zadanu točnost. Na kraju ćemo vlastite implementacije usporediti s ugrađenim rješavačima i pokazati dobitak koji donosi prilagodljiv korak.
  • QR dekompozicija s pivotiranjem 
    – QR dekompozicija temelj je numerički stabilnog rješavanja problema najmanjih kvadrata, ali u slučaju matrice nepunog ranga obična dekompozicija ne otkriva koji su stupci linearno zavisni. U radu ćemo izvesti QR dekompoziciju trima pristupima — klasičnim i modificiranim Gram–Schmidtovim postupkom, Householderovim reflektorima i Givensovim rotacijama — te usporediti njihovu numeričku stabilnost i cijenu. Zatim ćemo obraditi dekompoziciju s pivotiranjem stupaca, u kojoj se stupci biraju po opadajućoj normi ostatka, pa se dobiva rastav AP = QR s dijagonalom matrice R koja ne raste. Metode ćemo implementirati u MATLAB-u i pokazati kako se iz naglog pada dijagonalnih elemenata očitava numerički rang matrice, kako se biraju najinformativniji stupci i kako se rješava problem najmanjih kvadrata nepunog ranga. Usporedbom sa singularnom dekompozicijom pokazat ćemo granice ovog pristupa, uključujući poznate primjere matrica na kojima pivotiranje ne otkriva rang.
  • Računanje matrične ekponencijalne funkcije
    – Matrična eksponencijalna funkcija daje rješenje linearnog sustava diferencijalnih jednadžbi s konstantnim koeficijentima, no njezino je računanje klasičan primjer problema u kojem mnogi naizgled prirodni postupci numerički zakazuju. U radu ćemo obraditi glavne skupine metoda: sumiranje Taylorova reda, spektralnu dekompoziciju, pristup preko Schurove forme, te Padéovu aproksimaciju u kombinaciji s postupkom skaliranja i kvadriranja, koji je danas standard. Metode ćemo implementirati i usporediti na testnim matricama različite naravi — simetričnima, nenormalnima i s bliskim svojstvenim vrijednostima — mjereći točnost u odnosu na referentno rješenje i vrijeme računanja. Primjenu ćemo ilustrirati na rješavanju linearnih dinamičkih sustava.
  • Metoda Gaussovih eliminacija s potpunim pivotiranjem
    – Gaussova eliminacija bez pivotiranja može se slomiti i na dobro uvjetovanim sustavima, pa je izbor stožernog elementa ključan dio metode. U radu ćemo obraditi eliminaciju s potpunim pivotiranjem, u kojoj se u svakom koraku traži element najveće apsolutne vrijednosti u cijeloj preostaloj podmatrici, što vodi na rastav PAQ = LU. Usporedit ćemo je s parcijalnim pivotiranjem po faktoru rasta i po cijeni: potpuno pivotiranje traži kvadratno mnogo usporedbi u svakom koraku, ali daje znatno bolju teorijsku ogradu na rast elemenata. Pokazat ćemo i primjere matrica na kojima parcijalno pivotiranje daje eksponencijalni rast. U MATLAB-u ćemo izraditi vizualizaciju koraka metode, u kojoj se u svakom koraku prikazuju veličine elemenata matrice i označava izabrani stožerni element, te geometrijsku vizualizaciju sustava dviju jednadžbi s dvije nepoznanice, na kojoj se vidi presjek pravaca i kako se rješenje gubi kad su pravci gotovo paralelni.
  • Aproksimativna analitička rješenja harmoničkog oscilatora prigušenog kombinacijom
    linearnih i nelinearnih disipativnih sila

    – Prigušenje vibracija se najčešće opisuje silom koja je proporcionalna brzini
    (linearno prigušenje). U realnim sustavima su pored linearnih, u većoj ili manjoj mjeri,
    uvijek prisutne i nelinearne sile prigušenja, kao prigušenje proporcionalno kvadratu brzine
    (kvadratno prigušenje) i suho trenje (prigušenje neovisno o iznosu brzine, tzv.
    Coulombovo prigušenje). Već za najjednostavniji vibracijski sustav s jednim stupnjem
    slobode, tj. harmonički oscilator, nije moguće riješiti analitički jednadžbu gibanja koja
    uključuje sve tri navedene sile prigušenja. U ovom diplomskom radu ćemo, polazeći od
    veze disipacije energije i snage ukupne sile prigušenja, izvesti aproksimativna analitička
    rješenja za harmonički oscilator prigušen s tri navedene sile prigušenja. Usporedbom s
    numeričkim rješenjima, pokazat ćemo da dobivena aproksimativna analitička rješenja
    izvrsno opisuju slobodne vibracije sustava za raspon parametara (konstanti) prigušenja
    koji je relevantan za opis eksperimenata u temeljnim istraživanjima, ali i u tehnološkim
    primjenama. Demonstrirat ćemo kako se naša rješenja mogu iskoristiti da se iz
    eksperimentalnih podataka dobiju parametri svakog od tri tipa prigušenja.

 

Nastavne aktivnosti u zimskom semestru Akademske 2026./2027.

 

Linearna algebra I, predavanja

srijedom  10-12h,

 

Nastavne aktivnosti u ljetnom semestru Akademske 2025./2026.

Osnove teorije upravljanja s primjenama, predavanja

Utorkom 10-12 h

Redukcija modela i aproksimacijski pristupi,