A DDDAS Plume Monitoring System with Reduced Kalman Filter1

AbstractA new dynamic data-driven application system (DDDAS) is proposed in this article to dynamically estimate a concentration plume and to plan optimal paths for unmanned aerial vehicles (UAVs) equipped with environmental sensors. The proposed DDDAS dynamically incorporates measured data from UAVs into an environmental simulation while simultaneously steering measurement processes. The main idea is to employ a few time-evolving proper orthogonal decomposition (POD) modes to simulate a coupled linear system, and to simultaneously measure plume concentration and plume source distribution via a reduced Kalman filter. In order to maximize the information gain, UAVs are dynamically driven to hot spots chosen based on the POD modes using a greedy algorithm. We demonstrate the efficacy of the data assimilation and control strategies in a numerical simulation and a field test

Sensor Selection Based on Generalized Information Gain for Target Tracking in Large Sensor Networks

In this paper, sensor selection problems for target tracking in large sensor networks with linear equality or inequality constraints are considered. First, we derive an equivalent Kalman filter for sensor selection, i.e., generalized information filter. Then, under a regularity condition, we prove that the multistage look-ahead policy that minimizes either the final or the average estimation error covariances of next multiple time steps is equivalent to a myopic sensor selection policy that maximizes the trace of the generalized information gain at each time step. Moreover, when the measurement noises are uncorrelated between sensors, the optimal solution can be obtained analytically for sensor selection when constraints are temporally separable. When constraints are temporally inseparable, sensor selections can be obtained by approximately solving a linear programming problem so that the sensor selection problem for a large sensor network can be dealt with quickly. Although there is no guarantee that the gap between the performance of the chosen subset and the performance bound is always small, numerical examples suggest that the algorithm is near-optimal in many cases. Finally, when the measurement noises are correlated between sensors, the sensor selection problem with temporally inseparable constraints can be relaxed to a Boolean quadratic programming problem which can be efficiently solved by a Gaussian randomization procedure along with solving a semi-definite programming problem. Numerical examples show that the proposed method is much better than the method that ignores dependence of noises.Comment: 38 pages, 14 figures, submitted to Journa

Prototype Robot for Computer Vision and Control Systems Applications

This paper describes a robot designed and developed by a student in the context of an Electronic Engineering degree course. This robot is composed by three wheels, two of them can be controlled inde- pendently and the third one is used for stability. The robot also includes a webcam provided with pan and tilt control. This work was focused on the implementation of a prototype useful for academic research in the areas of Computer Vision and Control Systems Dynamics. In this document, the main characteristics of this robot are described.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Mechanical performances of twill kenaf woven fiber reinforced polyester composites

Natural fibres have the potential aspect to replace glass fibre reinforced composites. One of these fibers is kenaf. It is also one of the selected natural fibres that have bio resource profit regarding on their capability to absorb energy absorption especially. In order to prove the application of this fiber for the load-bearing application, the fiber in the form of yarn is weaved into fiber mat and reinforced with the plastic resin. This study focused on the twill yarn kenaf woven composite structure. Composites were prepared using the hand lay-up method with different type of orientation where the orientation is designed using Taguchi method. The hardened composites were cured for 24 hours in an ambient temperature before it was shaped according to ASTM D3039. The samples were then stressed uni-axially to obtain the stress-strain curves. The result shows the fiber orientations were significant factor in determining the performance of tensile strength. In this work, fiber mats are then optimized and the results showed that the values of tensile and modulus strength were 55.738 MPa and 5761.704 Joule, which is increased 3.77% and 4.23% for tensile strength and Young modulus, respectively. By comparing fracture mechanism before and after optimizations, there was clear decreasing fracture surface. It indicated that, the mechanical behavior performances of the twill woven kenaf reinforced composites can be effectively improved by this method