Open AccessComputing Different Realizations of Linear Dynamical Systems with Embedding Eigenvalue Assignment
Author(s) -
Gergely Szlobodnyik,
Gábor Szederkényi
Publication year - 2022
Publication title -
acta cybernetica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.143
H-Index - 18
eISSN - 2676-993X
pISSN - 0324-721X
DOI - 10.14232/actacyb.291870
Subject(s) - realizability , mathematics , state space , realization (probability) , eigenvalues and eigenvectors , stochastic matrix , state (computer science) , convexity , markov chain , dimension (graph theory) , discrete mathematics , sequence (biology) , combinatorics , algorithm , statistics , physics , quantum mechanics , biology , financial economics , economics , genetics
In this paper we investigate realizability of discrete time linear dynamical systems (LDSs) in fixed state space dimension. We examine whether there exist different Θ = (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.