Systems Of Linear Differential-algebraic Equations Research Articles

Impulse Transfer Matrix of a Time-Varying System of Differential-Algebraic Equations

A range of issues related to the impulse transfer matrix of a system of linear differential-algebraic equations is considered. For systems with infinitely differentiable coefficients, it is shown that this matrix can be represented as the sum of the impulse transfer matrices of its differential and algebraic subsystems. A form of a nondegenerate change of variables is found, which does not affect the form of the impulse transfer matrix. It is proposed to search for realizations of this matrix in the class of differential-algebraic equations of index 1 with separated differential and algebraic components. Necessary and sufficient conditions for the realizability of an impulse transfer matrix in the class of algebraic systems are obtained. The problem of construction methods and the dimension of minimal realizations of such a matrix is discussed under various assumptions.

On Solving System of Linear Differential-Algebraic Equations Using Reduction Algorithm

In this paper, we present a new reduction algorithm for solving system of linear differential-algebraic equations with power series coefficients. In the proposed algorithm, we transform the given system of differential-algebraic equations into another simple equivalent system using the elementary algebraic techniques. This algorithm would help to implement the manual calculations in commercial packages such as Mathematica, Maple, MATLAB, Singular, and Scilab. Maple implementation of the proposed algorithm is discussed, and sample computations are presented to illustrate the proposed algorithm.

Parameterized model order reduction for linear DAE systems via ε-embedding technique

In this paper, we present a new method in the reduction of large-scale linear differential-algebraic equation (DAE) systems. The approach is to first change the DAE system into a parametric ordinary differential equation (ODE) system via the ε-embedding technique. Next, based on parametric moment matching, we give the parameterized model order reduction (MOR) method to reduce this parametric system, and a new Arnoldi parameterized method is proposed to construct the column-orthonormal matrix. From the reduced-order parametric system, we get the reduced-order DAE system, which can preserve the structure of the original DAE system. Besides, the parametric moment matching for the reduced-order parametric systems is analyzed. Finally, the effectiveness of our method is successfully illustrated via two numerical examples.

Differential Controllability of Linear Systems of Differential-algebraic Equations

Differential Controllability of Linear Systems of Differential-algebraic Equations

Asymptotic integration of singularly perturbed linear systems of differential-algebraic equations

Asymptotic integration of singularly perturbed linear systems of differential-algebraic equations

Stabilization of Switched Linear Differential Algebraic Equations and Periodic Switching

We investigate the stabilizability of switched linear systems of differential-algebraic equations (DAEs). For such systems we introduce a parameterized family of switched ordinary differential equations that approximate the dynamic behavior of the switched DAE. A necessary and sufficient criterion for the stabilizability of a switched DAE system using time-dependent switching is obtained in terms of these parameterized approximations. Furthermore, we provide conditions for the stabilizability of switched DAEs via fast switching as well as using solely the consistency projectors of the constituent systems. The stabilization of switched DAEs with commuting vector fields is also analyzed.

Index for linear systems of differential-algebraic equations with partial derivatives

We investigate time-varying linear differential algebraic equations with partial derivatives. We introduce concept of insolubility index as the least possible order of the differential operator which transforms the initial system into a structural form with separated the “algebraic” and “differential” subsystems. The approach does not assume the existence of differential indexes with respect to independent variables.

An efficient algorithm for the solution of a coupled Sylvester equation appearing in descriptor systems

Descriptor systems consisting of a large number of differential–algebraic equations (DAEs) usually arise from the discretization of partial differential–algebraic equations. This paper presents an efficient algorithm for solving the coupled Sylvester equation that arises in converting a system of linear DAEs to ordinary differential equations. A significant computational advantage is obtained by exploiting the structure of the involved matrices. The proposed algorithm removes the need to solve a standard Sylvester equation or to invert a matrix. The improved performance of this new method over existing techniques is demonstrated by comparing the number of floating-point operations and via numerical examples.

Application of matrix polynomials to the analysis of linear differential-algebraic equations of higher order

We consider systems of linear differential-algebraic equations of order ≥ 2 and present conditions under which there exist nonsingular transformations splitting the system into systems of linear ordinary differential equations of lower order and, possibly, an algebraic part.

Implicit-system approach to the robust stability for a class of singularly perturbed linear systems

Asymptotic stability and the complex stability radius of a class of singularly perturbed systems of linear differential-algebraic equations (DAEs) are studied. The asymptotic behavior of the stability radius for a singularly perturbed implicit system is characterized as the parameter in the leading term tends to zero. The main results are obtained in direct and short ways which involve some basic results in linear algebra and classical analysis, only. Our results can be extended to other singular perturbation problems for DAEs of more general form.

Adjoint Sensitivity Analysis for Differential-Algebraic Equations: The Adjoint DAE System and Its Numerical Solution

An adjoint sensitivity method is presented for parameter-dependent differential-algebraic equation systems (DAEs). The adjoint system is derived, along with conditions for its consistent initialization, for DAEs of index up to two (Hessenberg). For stable linear DAEs, stability of the adjoint system (for semi-explicit DAEs) or of an augmented adjoint system (for fully implicit DAEs) is shown. In addition, it is shown for these systems that numerical stability is maintained for the adjoint system or for the augmented adjoint system.

Floquet theory and non-linear perturbation analysis for oscillators with differential-algebraic equations

Oscillators are key components of electronic systems. In RF communication systems, they are used for frequency translation of information signals and for channel selection, and in digital electronic systems, they are used as a time reference, i.e. a clock signal, in order to synchronize operations. Undesired perturbations in practical electronic systems adversely affect the spectral and timing properties of oscillators, which is a key performance limiting factor, being a major contributor to bit-error-rate (BER) of RF communication systems, and creating synchronization problems in clocked and sampled-data systems. Characterizing how perturbations affect oscillators is therefore crucial for practical applications. The traditional approach to analysing perturbed nonlinear systems (i.e. linearization) is not valid for oscillators. In this paper, we present a theory and efficient numerical methods, for non-linear perturbation and noise analysis of oscillators described by a system of differential-algebraic equations (DAEs). Our techniques can be used in characterizing phase noise and timing jitter due to intrinsic noise in IC devices, and evaluating the effect of substrate and supply noise on the timing properties of practical oscillators. In this paper, we also establish novel results for periodically time-varying systems of linear DAEs, which we rely on in developing the above theory and the numerical methods. Copyright © 2000 John Wiley & Sons, Ltd.

State Maps for Linear Systems

Modeling of physical systems consists of writing the equations describing a phenomenon and yields as a result a set of differential-algebraic equations. As such, state-space models are not a natural starting point for modeling, while they have utmost importance in the simulation and control phase. The paper addresses the problem of computing state variables for systems of linear differential-algebraic equations of various forms. The point of view from which the problem is considered is the behavioral one, as put forward in [J. C. Willems, Automatica J. IFAC, 22 (1986), pp. 561--580; Dynamics Reported, 2 (1989), pp. 171--269; IEEE Trans. Automat. Control, 36 (1991), pp. 259--294].

State Maps for Linear Systems

Modelling of physical systems produces as a result a set of differentialalgebraic equations (generally of higher order). As such, state space models are not a natural starting point for modelling, while they have utmost importance in the simulation and control phase. The paper addresses the problem of computing state representations for systems of linear differential-algebraic equations from the behavioral point of view.