Office: University Hall 2753
Dr. Ben G. Fitzpatrick is the Clarence J. Wallen, S. J. Professor of Mathematics at Loyola Marymount University. His interests are in applied mathematics. Dr. Fitzpatrick received his Ph.D. and Sc. M. from Brown University in 1988 and 1986, respectively, and his M.P.S. and B.S. from Auburn University in 1983 and 1981, respectively.
Brown University: Ph.D., Applied Mathematics 1988
Auburn University: M.A., Probability and Statistics 1983
Auburn University: B.Sc., Applied Mathematics 1981
Areas of Expertise (7)
Dynamics and Control
Industry Expertise (3)
- Tempest Technologies
In recent years a class of adaptive schemes has been developed for suppressing periodic disturbance signals with unknown frequencies, phases, and amplitudes. The stability and robustness of these schemes with respect to inevitable unmodeled dynamics and noise disturbances in the absence of persistently exciting signals has not been established despite successful simulation results and implementations.
This paper investigates noise attenuation problems for systems with unmodelled dynamics and unknown noise characteristics. A unique methodology is introduced that employs signal estimation in one phase, followed by control design for noise rejection.
A number of college presidents have endorsed the Amethyst Initiative, a call to consider lowering the minimum legal drinking age (MLDA). Our objective is to forecast the effect of the Amethyst Initiative on college drinking.
Adaptive filtering algorithms are investigated when system models are subject to model structure errors and regressor signal perturbations. System models for practical applications are often approximations of high-order or nonlinear systems, introducing model structure uncertainties. Measurement and actuation errors cause signal perturbations, which in turn lead to uncertainties in regressors of adaptive filtering algorithms.
The present paper presents a preliminary approach to the modeling of dynamic properties of the spatial assortment of alcohol outlets using agent based techniques. Individual drinkers and business establishments are the core agent types. Drinkers assort themselves by frequenting establishments due to spatial and social (niche) motivations. We examine a number of questions concerning the feedback relationships between establishments targeting a particular niche clientele and the individuals seeking more desirable places to obtain alcohol.
In this paper, we examine three separate approaches to analyze the spatial dispersion of a subsurface contaminant. These methods are contrasted against traditional models to demonstrate their feasibility and usefulness. Lastly, numerical simulations illustrate the effectiveness of these approaches.