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  • 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
    Descripción/Resumen:
    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.
    Creador/Autor:
    Weller, Tanchum; Cohen, Kelly, and Ben-Asher, Joseph
    Peticionario:
    Kelly Cohen
    Fecha modificada:
    02/03/2017
    Fecha modificada:
    04/05/2017
    Fecha de creacion:
    2001-11
    Licencia:
    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
    Descripción/Resumen:
    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.
    Creador/Autor:
    Cohen, Kelly; Sabo, Chelsea, and Kingston, Derek
    Peticionario:
    Kelly Cohen
    Fecha modificada:
    02/03/2017
    Fecha modificada:
    04/05/2017
    Fecha de creacion:
    2014-01
    Licencia:
    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
    Descripción/Resumen:
    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.
    Creador/Autor:
    Sharma, Balaji R.; Cohen, Kelly; Ernest, Nicholas; Kumar, Manish, and Kivelevitch, Elad
    Peticionario:
    Kelly Cohen
    Fecha modificada:
    02/03/2017
    Fecha modificada:
    04/05/2017
    Fecha de creacion:
    2014-01
    Licencia:
    All rights reserved