The local output regulation problem: convergence region estimates

In this paper, the problem of local output regulation is considered. The presented results answer the question: given a controller solving the local output regulation problem, how to estimate the set of admissible initial conditions for which this controller makes the regulated output converge to zero. Theoretical estimation results and an estimation procedure explaining the application of these results in practice are presented. An example of the disturbance rejection problem for a mechanical system (TORA system) is given as an illustration

The global output regulation problem: an incremental stability approach

We present a global solution to the output regulation problem for a class of nonlinear systems. The solution is based on the incremental stability property. The question of existence of the proposed solution can be answered by checking solvability of the regulator equations and feasibility of certain linear matrix inequalities

Alternative Methods in Spectral Factorization. A Modeling and Design Tool

Spectral factorization can be used to recover the complex transfer function of a linear, causal, stable, minimum-phase system from merely its amplitude information. Two different approaches are presented, resulting in two consistent expressions for the complex transfer function. Firstly, an approach using Fourier theory is followed (Papoulis, 1977; Priestley, 1981). Secondly, a new approach using potential theory results is presented. Spectral factorization can be successfully used as a modeling tool. Moreover, its capability to serve as a design tool is emphasized. These fields of application are illustrated by means of examples

Convergency and regulation

No abstract

An Integrative Framework of the Factors Affecting Process Model Understanding: A Learning Perspective

Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies

Model reduction for linear delay systems using a delay-independent balanced truncation approach

A model reduction approach for asymptotically stable linear delay-differential equations is presented in this paper. Specifically, a balancing approach is developed on the basis of energy functionals that provide (bounds on) a measure of energy related to observability and controllability, respectively. The reduced-order model derived in this way is again a delay-differential equation, such that the method is structure preserving. In addition, asymptotic stability is preserved and an a priori bound on the reduction error is derived, providing a measure of accuracy of the reduction. The results are illustrated by means of application on an example

Identification of nonlinear phenomena in a stochastically excited beam system with impact

The response of strongly nonlinear dynamic systems to stochastic excitation exhibits many interesting characteristics. In this paper, an impacting beam system under broad and small banded, Gaussian noise excitation is investigated numerically as well as experimentally. The emphasis lies on frequency domain characteristics. Phenomena like multiple resonance frequencies and stochastic equivalents of harmonic and subharmonic solutions are found. A better understanding of such stochastic response characteristics is obtained by a comparison with nonlinear periodic response features. It is shown that these stochastic response phenomena can provide valuable information on periodic response characteristics of the system