Robust finite-horizon Kalman filtering for uncertain discrete-time systems

In this note, we propose a design for a robust finite-horizon Kalman filtering for discrete-time systems suffering from uncertainties in the modeling parameters and uncertainties in the observations process (missing measurements). The system parameter uncertainties are expected in the state, output and white noise covariance matrices. We find the upper-bound on the estimation error covariance and we minimize the proposed upper-bound.

Finding higher symmetries of differential equations using the MAPLE package DESOLVII

We present and describe, with illustrative examples, the MAPLE computer algebra package DESOLVII, which is a major upgrade of DESOLV. DESOLVII now includes new routines allowing the determination of higher symmetries (contact and Lie-Backlund) for systems of both ordinary and partial differential equations.

Discrete event simulation enabled high level emulation of a distribution centre

Emulation facilitates the testing of control systems through the use of a simulation model. Typically emulation has focused on low level control, to ensure that resources within a system are commissioned correctly. Higher level control that deals with complex issues such as throughput, in-system time and stacking, has not received as much attention. In this paper, a higher level agent-based emulation framework was proposed. Then an emulation model for a distribution centre is described that can test distribution centre level algorithms directly. This methodology also allows playback of real world operations, making it an ideal tool to analyse problems with performance of commissioned systems.

A discrete simulation approach to spatial allocation of commodity production for revenue optimisation over a local region

A simulation approach is described for the spatial allocation of crops across a region in order to maximise total revenue. The model uses inputs from GIS-based land suitability analysis to provide data on yields for a range of commodities, where the land suitability for the crops can be determined by either biophysical models or multi-criteria analysis. The objective of the study was to gain some indication of the magnitude of improvement possible in revenue, based on the convergence results for the optimisation (subject to estimated production quantities and market prices). The basic structure of the model allows for scaling up to larger problems with additional inputs and finer cell resolution. The software produces a visualisation of crop spatial allocation across the region and is compatible with statistical uncertainty analysis. The results of model simulations revealed a significant increase in revenue is possible using this approach and, when projected over the full region, suggests the possibility of significant economic benefits.

A protocol for a discrete choice experiment: understanding preferences of patients with cancer towards their cancer care across metropolitan and rural regions in Australia.

Medical decision-making in oncology is a complicated process and to date there are few studies examining how patients with cancer make choices with respect to different features of their care. It is also unknown whether patient choices vary by geographical location and how location could account for observed rural and metropolitan cancer differences. This paper describes an ongoing study that aims to (1) examine patient and healthcare-related factors that influence choices of patients with cancer; (2) measure and quantify preferences of patients with cancer towards cancer care using a discrete choice experiment (DCE) and (3) explore preference heterogeneity between metropolitan and rural locations.

H∞ observer-based control for discrete-time one-sided Lipschitz systems with unknown inputs

This paper investigates the problem of robust observer-based stabilization for a class of one-sided nonlinear discrete-time systems subjected to unknown inputs. We propose a simple simultaneous state and input estimator. A nonlinear controller is then proposed to compensate for the effects of unknown inputs and to ensure asymptotic stability in a closed loop. Several mathematical artifacts are used to deduce stability conditions expressed in terms of linear matrix inequalities. To show high performances of the proposed technique, a relevant example is provided with comparisons to recent results.

FracSym: automated symbolic computation of Lie symmetries of fractional differential equations

In this paper, we present an algorithm for the systematic calculation of Lie point symmetries for fractional order differential equations (FDEs) using the method as described by Buckwar & Luchko (1998) and Gazizov, Kasatkin & Lukashchuk (2007, 2009, 2011). The method has been generalised here to allow for the determination of symmetries for FDEs with n independent variables and for systems of partial FDEs. The algorithm has been implemented in the new MAPLE package FracSym (Jefferson and Carminati 2013) which uses routines from the MAPLE symmetry packages DESOLVII (Vu, Jefferson and Carminati, 2012) and ASP (Jefferson and Carminati, 2013). We introduce FracSym by investigating the symmetries of a number of FDEs; specific forms of any arbitrary functions, which may extend the symmetry algebras, are also determined. For each of the FDEs discussed, selected invariant solutions are then presented. © 2013 Elsevier B.V. All rights reserved.