Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Application of Volterra series in nonlinear mechanical system identification and in structural health monitoring problems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mathematical modeling and control of population systems: Applications in biological pest control

The aim of this paper is to apply methods from optimal control theory, and from the theory of dynamic systems to the mathematical modeling of biological pest control. The linear feedback control problem for nonlinear systems has been formulated in order to obtain the optimal pest control strategy only through the introduction of natural enemies. Asymptotic stability of the closed-loop nonlinear Kolmogorov system is guaranteed by means of a Lyapunov function which can clearly be seen to be the solution of the Hamilton-Jacobi-Bellman equation, thus guaranteeing both stability and optimality. Numerical simulations for three possible scenarios of biological pest control based on the Lotka-Volterra models are provided to show the effectiveness of this method. (c) 2007 Elsevier B.V. All rights reserved.

Caracterização experimental de sistemas mecânicos com comportamento não-linear

Pós-graduação em Engenharia Mecânica - FEIS

Interaction strengths and net effects in food web models

Understanding how dynamic ecological communities respond to anthropogenic drivers of change such as habitat loss and fragmentation, climate change and the introduction of alien species requires that there is a theoretical framework able to predict community dynamics. At present there is a lack of empirical data that can be used to inform and test predictive models, which means that much of our knowledge regarding the response of ecological communities to perturbations is obtained from theoretical analyses and simulations. This thesis is composed of two strands of research: an empirical experiment conducted to inform the scaling of intraspecific and interspecific interaction strengths in a three species food chain and a series of theoretical analyses on the changes to equilibrium biomass abundances following press perturbations. The empirical experiment is a consequence of the difficulties faced when parameterising the intraspecific interaction strengths in a Lotka-Volterra model. A modification of the dynamic index is used alongside the original dynamic index to estimate intraspecific interactions and interspecific interaction strengths in a three species food. The theoretical analyses focused on the effect of press perturbations to focal species on the equilibrium biomass densities of all species in the community; these perturbations allow for the quantification of a species total net effect. It was found that there is a strong and consistent positive relationship between a species body size and its total net effect for a set of 97 synthetic food webs and also for the Ythan Estuary and Tuesday Lake food webs (empirically described food webs). It is shown that ecological constraints (due to allometric scaling) on the magnitude of entries in the community matrix cause the patterns observed in the inverse community matrix and thus explain the relationship between a species body mass and its total net effect in a community.

Higher order Painleve equations and their symmetries via reductions of a class of integrable models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Toda and Volterra lattice equations from discrete symmetries of KP hierarchies

The discrete models of the Toda and Volterra chains are being constructed out of the continuum two-boson KP hierarchies. The main tool is the discrete symmetry preserving the Hamiltonian structure of the continuum models. The two-boson currents of KP hierarchy are being associated with sites of the corresponding chain by successive actions of discrete symmetry.

Estabilidade global e bifurcação de Hopf em um modelo de HIV baseado em sistemas do tipo Lotka-Volterra

Pós-graduação em Matematica Aplicada e Computacional - FCT

Integrating OpenMI and Uncertweb:managing uncertainty in OpenMI models

OpenMI is a widely used standard allowing exchange of data between integrated models, which has mostly been applied to dynamic, deterministic models. Within the FP7 UncertWeb project we are developing mechanisms and tools to support the management of uncertainty in environmental models. In this paper we explore the integration of the UncertWeb framework with OpenMI, to assess the issues that arise when propagating uncertainty in OpenMI model compositions, and the degree of integration possible with UncertWeb tools. In particular we develop an uncertainty-enabled model for a simple Lotka-Volterra system with an interface conforming to the OpenMI standard, exploring uncertainty in the initial predator and prey levels, and the parameters of the model equations. We use the Elicitator tool developed within UncertWeb to identify the initial condition uncertainties, and show how these can be integrated, using UncertML, with simple Monte Carlo propagation mechanisms. The mediators we develop for OpenMI models are generic and produce standard Web services that expose the OpenMI models to a Web based framework. We discuss what further work is needed to allow a more complete system to be developed and show how this might be used practically.

Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in modern power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Northern Ireland.