Ferdinand Svaricek

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— Recently, the concept of strong structural control-lability has attracted renewed attention. In this context the existing literature to strong structural controllability has been revisited and some of the previous results have been found to be incorrect. Therefore, in this paper an overview of the previous results on strong structural controllability,(More)
— In this paper, we extend the notion of strong structural controllability of linear time-invariant systems, a property that requires the controllability of each system in a specific class given by the zero-nonzero pattern of the system matrices, to the linear time-varying case ˙ x(t) = A(t) · x(t) + B(t) · u(t), where A and B are matrices of analytic(More)
— This paper proposes a tracking controller based on the concept of flat inputs and a dynamic compensator. Flat inputs represent a dual approach to flat outputs. In contrast to conventional flatness-based control design, the regulated output may be a non-flat output, or the system may be non-flat. The method is applicable to observable systems with stable(More)
—In this note we consider continuous-time systems ˙ x(t) = A(t)x(t) + B(t)u(t), y(t) = C(t)x(t) + D(t)u(t) as well as discrete-time systems x(t + 1) = A(t)x(t) + B(t)u(t), y(t) = C(t)x(t) + D(t)u(t) whose coefficient matrices A, B, C and D are not exactly known. More precisely, all that is known about the systems is their nonzero pattern, i.e., the(More)
— We prove that strong structural controllability of a pair of structural matrices (A, B) can be verified in time linear in n + r + ν, where A is square, n and r denote the number of columns of A and B, respectively, and ν is the number of non-zero entries in (A, B). We also present an algorithm realizing this bound, which depends on a recent, high-level(More)
In this note we consider continuous-time systems ˙ x(t) = A(t)x(t) + B(t)u(t) as well as discrete-time systems x(t + 1) = A(t)x(t) + B(t)u(t) whose coefficient matrices A and B are not exactly known. More precisely, all that is known about the systems is their nonzero pattern, i.e., the locations of the nonzero entries in the coefficient matrices. We(More)