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  • Genetic Fuzzy Trees and their Application Towards Autonomous Training and Control of a Squadron of Unmanned Combat Aerial Vehicles

    Article thumbnail: Genetic Fuzzy Trees and their Application Towards Autonomous Training and Control of a Squadron of Unmanned Combat Aerial Vehicles
    Type:
    Article
    Description/Abstract:
    This study introduces the technique of Genetic Fuzzy Trees (GFTs) through novel application to an air combat control problem of an autonomous squadron of Unmanned Combat Aerial Vehicles (UCAVs) equipped with next-generation defensive systems. GFTs are a natural evolution to Genetic Fuzzy Systems, in which multiple cascading fuzzy systems are optimized by genetic methods. In this problem a team of UCAV's must traverse through a battle space and counter enemy threats, utilize imperfect systems, cope with uncertainty, and successfully destroy critical targets. Enemy threats take the form of Air Interceptors (AIs), Surface to Air Missile (SAM) sites, and Electronic WARfare (EWAR) stations. Simultaneous training and tuning a multitude of Fuzzy Inference Systems (FISs), with varying degrees of connectivity, is performed through the use of an optimized Genetic Algorithm (GA). The GFT presented in this study, the Learning Enhanced Tactical Handling Algorithm (LETHA), is able to create controllers with the presence of deep learning, resilience to uncertainties, and adaptability to changing scenarios. These resulting deterministic fuzzy controllers are easily understandable by operators, are of very high performance and efficiency, and are consistently capable of completing new and different missions not trained for.
    Creator/Author:
    Schumacher, Corey; Cohen, Kelly; Ernest, Nicholas; Casbeer, David, and Kivelevitch, Elad
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2015-05
    License:
    All rights reserved

  • Spatio-temporal estimation of wildfire growth

    Article thumbnail: Spatio-temporal estimation of wildfire growth
    Type:
    Article
    Description/Abstract:
    This work presents a methodology for real-time estimation of wildland fire growth, utilizing a fire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deployability.
    Creator/Author:
    Sharma, Balaji R.; Cohen, Kelly, and Kumar, Manish
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2013-10
    License:
    All rights reserved

  • Optimal Fireline Generation for Wildfire Fighting in Uncertain and Heterogeneous Environment

    Article thumbnail: Optimal Fireline Generation for Wildfire Fighting in Uncertain and Heterogeneous Environment
    Type:
    Article
    Description/Abstract:
    Fire is a natural component of many ecosystems but wildland fires often do pose serious threats to public safety, properties and natural resources. Forest fire acts as a dominant factor in reshaping of terrain and change of the ecosystem of a particular area. The total damage due to wildland fire shows an increasing trend over the past decade. Forest Fire Decision Support Systems (FFDSS) have been developed for the last thirty years all over the world that supplies valuable information on forest fire detection, fire behavior and other aspects of forest fires but lacks in developing intelligent fire suppression strategies. In this paper, an effort has been made to generate intelligent fire suppression strategies with efficient resource allocation using the Genetic Algorithm based optimization tool in a heterogeneous and uncertain scenario. The goal of this research is to perform intelligent resource allocation along with the generation of optimal firelines that minimizes the total burned area due to wildland fire. The solutions generated at each generations of the Genetic Algorithm (GA) are used to build the firelines in a heterogeneous terrain where advanced forest fire propagation model is used to evaluate the fitness values of each generated solutions. The optimal firelines thus obtained through the Simulation-Optimization technique minimizes the total damage due to wildland fire and eliminates the chance of any fire escape i.e., firefront reaching the fireline positions before they are built. Such techniques integrated with the existing FFDSS hold promise in effectively controlling forest fires.
    Creator/Author:
    Manish, Kumar; Cohen, Kelly, and HomChaudhuri, Baisravan
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2010-07
    License:
    All rights reserved

  • Fuzzy logic control applications for second order problems with low damping

    Article thumbnail: Fuzzy logic control applications for second order problems with low damping
    Type:
    Article
    Description/Abstract:
    A general methodology has been developed for the design of a robust control law for a family of lightly damped second order problems. In this research effort, the passivity approach has been extended to systems having non-collocated input/output pairs by introducing an observer that incorporates the nominal dynamical model of the plant. The developed passive observer-based control law emulates numerous dynamic vibration absorbers which are tuned to a targeted frequency using classical methods and the tuning ratios are time-invariant. However, the uniqueness of this approach is that the damping parameters of the emulated absorbers are continuously varied by means of a fuzzy logic control algorithm to provide near minimum-time suppression of vibration. The developed approach is applied to both several benchmarks in the field of structural dynamics as well as experiments using piezo-ceramic sensors and actuators. Results show that this methodology provides stability and performance robustness on the one hand as well as requiring relatively low amount of actuation authority for desired nominal plant closeloop behavior.
    Creator/Author:
    Weller, Tanchum; Cohen, Kelly, and Ben-Asher, Joseph
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2001-11
    License:
    All rights reserved

  • A Formulation and Heuristic Approach to Task Allocation and Routing of UAVs under Limited Communication

    Article thumbnail: A Formulation and Heuristic Approach to Task Allocation and Routing of UAVs under Limited Communication
    Type:
    Article
    Description/Abstract:
    Unmanned Air Vehicle (UAV) teams are anticipated to provide surveillance support through algorithms, software, and automation. It is desirable to have algorithms that compute effective and efficient routes for multiple UAVs across a variety of missions. These algorithms must be realizable, practical, and account for uncertainties. In surveillance missions, UAVs act as mobile wireless communication nodes in a larger, underlying network consisting of targets where information is to be collected and base stations where information is to be delivered. The role of UAVs in these networks has primarily been to maintain or improve connectivity while undervaluing routing efficiency. Moreover, many current routing strategies for UAVs ignore communication constraints even though neglecting communication can lead to suboptimal tour designs. Generating algorithms for autonomous vehicles that work effectively despite these communication restrictions is key for the future of UAV surveillance missions. A solution is offered here based on a variation of the traditional vehicle routing problem and a simple communication model. In this work, the new routing formulation is defined, analyzed, and a heuristic approach is motivated and described. Simulation results show that the heuristic algorithm gives near-optimal results in real-time, allowing it to be used for large problem sizes and extended to dynamic scenarios.
    Creator/Author:
    Cohen, Kelly; Sabo, Chelsea, and Kingston, Derek
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2014-01
    License:
    All rights reserved

  • A Hierarchical Market Solution to the Min–Max Multiple Depots Vehicle Routing Problem

    Article thumbnail: A Hierarchical Market Solution to the Min–Max Multiple Depots Vehicle Routing Problem
    Type:
    Article
    Description/Abstract:
    The problem of assigning a group of Unmanned Aerial Vehicles (UAVs) to perform spatially distributed tasks often requires that the tasks will be performed as quickly as possible. This problem can be defined as the Min–Max Multiple Depots Vehicle Routing Problem (MMMDVRP), which is a benchmark combinatorial optimization problem. In this problem, UAVs are assigned to service tasks so that each task is serviced once and the goal is to minimize the longest tour performed by any UAV in its motion from its initial location (depot) to the tasks and back to the depot. This problem arises in many time-critical applications, e.g. mobile targets assigned to UAVs in a military context, wildfire fighting, and disaster relief efforts in civilian applications. In this work, we formulate the problem using Mixed Integer Linear Programming (MILP) and Binary Programming and show the scalability limitation of these formulations. To improve scalability, we propose a hierarchical market-based solution (MBS). Simulation results demonstrate the ability of the MBS to solve large scale problems and obtain better costs compared with other known heuristic solution.
    Creator/Author:
    Sharma, Balaji R.; Cohen, Kelly; Ernest, Nicholas; Kumar, Manish, and Kivelevitch, Elad
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2014-01
    License:
    All rights reserved

  • Synthesis of Acetic Acid Via CO2-CH4 Reformation and Carbonylation of Methanol

    Image thumbnail: Synthesis of Acetic Acid Via CO2-CH4 Reformation and Carbonylation of Methanol
    Type:
    Image
    Description/Abstract:
    The purpose of this project is to consider and evaluate the economic attractiveness of a process producing 250,000 lb/h of acetic acid by the selective carbonylation of methanol via carbon monoxide with the use of an iridium tri-iodide catalyst. Initial cost estimates of this process will be completed prior to the completed rigorous design to ensure the process is economically viable and meets product specifications. A full cost analysis will then be made on the initial design to further verify the process will meet product specifications and is economically attractive to the business. A recommendation to continue investigating will be made based on the analysis of the investment cost and annual operating costs of this reaction/separation system. An economic analysis was performed on the selected design. The total capital cost for this project is $145 million, with a yearly utility and incremental cost of $62 million and $90 million, respectively. The required ten-year return on investment was found to be 15%, when the Acetic Acid is sold at a price of $437 /ton. When the Acetic Acid is sold at $745/ton (achieves 15% 1-year ROI), an ROI of 547% is achieved for a 10-year period. In order to achieve a five-year ROI of 15%, the selling price of Acetic Acid is only increased to roughly $455/ton.
    Creator/Author:
    Kleiman, Christopher; Buchanan, Sean; Grunwald, Stephan, and Metzger, Devin
    Submitter:
    Stephen W. Thiel
    Date Uploaded:
    05/18/2015
    Date Modified:
    04/29/2016
    License:
    All rights reserved

  • A Drying Model of a Vibro-Separator

    Etd thumbnail: A Drying Model of a Vibro-Separator
    Type:
    Etd
    Description/Abstract:
    Vibro-separators are widely used to separate solid particles from slurries and/or to size segregate the dried product. In this thesis, a mathematical model was developed to theoretically evaluate the vacuum drying of the collected solid on the screen of a vibro-separator.
    Creator/Author:
    Yang, Yuelei
    Submitter:
    Graduate School
    Date Uploaded:
    12/12/2016
    Date Modified:
    05/23/2019
    Date Created:
    1999
    License:
    Attribution-NonCommercial-NoDerivs 4.0 International

  • A computational study of the dynamic propagation of two offset cracks using the phase field method

    Article thumbnail: A computational study of the dynamic propagation of two offset cracks using the phase field method
    Type:
    Article
    Description/Abstract:
    The study of the propagation of multiple cracks is essential to modeling and predicting structural integrity. The interaction between two cracks depends on a number of factors such as the domain geometry, the relative crack sizes and the separation between the two crack tips. In this paper, we study the interaction between two dynamically propagating cracks. We use the phase field method to track the crack paths, since this method can handle complex crack behavior such as crack branching, without any ad hoc criteria for crack evolution. The results from our dynamic simulations indicate that, unlike crack inter- action under quasi-static or fatigue loading, the presence of another crack does not accelerate crack propagation when dynamic loads are applied. However, some similarities in the crack topologies are observed for both quasi-static and dynamic loading.
    Creator/Author:
    Kumar Vemaganti and Sai Deogekar
    Submitter:
    Kumar Vemaganti
    Date Uploaded:
    10/11/2017
    Date Modified:
    10/11/2017
    License:
    All rights reserved

  • On the inference of viscoelastic time constants from stress relaxation experiments

    Article thumbnail: On the inference of viscoelastic time constants from stress relaxation experiments
    Type:
    Article
    Description/Abstract:
    Several constitutive theories have been proposed in the literature to model the viscoelastic response of soft tissue, including widely used rheological constitutive models. These models are characterized by certain parameters (“time constants”) that define the time scales over which the tissue relaxes. These parameters are primarily obtained from stress relaxation experiments using curve-fitting techniques. However, the question of how best to estimate these time constants remains open. As a step towards answering this question, we develop an optimal experimental design approach based on ideas from information geometry, namely Fisher information and Kullback-Leibler divergence. Tissue is modeled as a standard linear solid and described using a one- or two-term Prony series. Treating the time constants as unknowns, we develop expressions for the Fisher information and Kullback-Leibler divergence that allow us to maximize information gain from experimental data. Based on the results of this study, we propose that the largest time constant estimated from a stress relaxation experiment for a linear viscoelastic material should be at most one-fifth of the total time of the experiment in order to maximize information gain.
    Creator/Author:
    Kumar Vemaganti and Sandeep Madireddy
    Submitter:
    Kumar Vemaganti
    Date Uploaded:
    10/11/2017
    Date Modified:
    10/11/2017
    License:
    All rights reserved