%P 585-611 %C Szeged %O Bibliogr.: p. 606-609. ; ill. ; ĂśsszefoglalĂĄs angol nyelven %T Computing different realizations of linear dynamical systems with embedding eigenvalue assignment %J Acta cybernetica %A Szlobodnyik Gergely %A SzederkĂŠnyi GĂĄbor %N 3 %D 2022 %I University of Szeged, Institute of Informatics %L acta75625 %K SzĂĄmĂtĂĄstechnika, ProgramozĂĄs, Algoritmus %V 25 %X In this paper we investigate realizability of discrete time linear dynamical systems (LDSs) in fixed state space dimension. We examine whether there exist different Î = (A,B,C,D) state space realizations of a given Markov parameter sequence Y with fixed B, C and D state space realization matrices. Full observation is assumed in terms of the invertibility of output mapping matrix C. We prove that the set of feasible state transition matrices associated to a Markov parameter sequence Y is convex, provided that the state space realization matrices B, C and D are known and fixed. Under the same conditions we also show that the set of feasible Metzler-type state transition matrices forms a convex subset. Regarding the set of Metzler-type state transition matrices we prove the existence of a structurally unique realization having maximal number of non-zero off-diagonal entries. Using an eigenvalue assignment procedure we propose linear programming based algorithms capable of computing different state space realizations. By using the convexity of the feasible set of Metzler-type state transition matrices and results from the theory of non-negative polynomial systems, we provide algorithms to determine structurally different realization. Computational examples are provided to illustrate structural non-uniqueness of network-based LDSs.