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- Type:
- Image
- 摘抄:
- Comanthus cf. C. suavia
- 作者:
- Meyer, David L.
- 提交者:
- David L. Meyer
- 上传日期:
- 02/14/2017
- 更改日期:
- 02/14/2017
- 创建:
- 2017-02-14
- 证书:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- 摘抄:
- Oxycomanthus comanthipinna (?)
- 作者:
- Meyer, David L.
- 提交者:
- David L. Meyer
- 上传日期:
- 02/14/2017
- 更改日期:
- 02/14/2017
- 创建:
- 2017-02-14
- 证书:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- 摘抄:
- Comanthus parvicirrus, center individual; right, Phanogenia gracilis
- 作者:
- Meyer, David L.
- 提交者:
- David L. Meyer
- 上传日期:
- 02/13/2017
- 更改日期:
- 02/13/2017
- 创建:
- 2017-02-13
- 证书:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- 摘抄:
- Comanthus parvicirrus
- 作者:
- Meyer, David L.
- 提交者:
- David L. Meyer
- 上传日期:
- 02/13/2017
- 更改日期:
- 02/13/2017
- 创建:
- 2017-02-13
- 证书:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- 摘抄:
- Comanthus alternans (upper individual), with Oxycomathus bennetti (lower);lower rt: Phanogenia gracilis
- 作者:
- Meyer, David L.
- 提交者:
- David L. Meyer
- 上传日期:
- 02/13/2017
- 更改日期:
- 02/13/2017
- 创建:
- 2017-02-13
- 证书:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Article
- 摘抄:
- A genetic algorithm was used to optimize performance of a fuzzy inference system acting as a controller for a magnetically actuated CubeSat. A solely magnetically controlled satellite is a nonlinear, underactuated system for which the uncontrollable axis varies as a function of orbit position and attitude; variation is approximately periodic with orbit position. Therefore, controllability is not guaranteed, making solely magnetic control a less than ideal option for spacecraft requiring a high degree of pointing accuracy or spacecraft subject to relatively large disturbances. However, for small spacecraft, such as CubeSats, with modest pointing and disturbance rejection requirements, solely magnetic actuation is a good option. The genetic-algorithm-tuned fuzzy controller solution was compared to a similar linear quadratic regulator solution that was tuned to minimize the cost function used by the genetic algorithm. Both were optimized with respect to a single set of initial conditions. The genetic-algorithm-tuned fuzzy controller was found to be a lower-cost solution than the linear quadratic regulator for the optimized set of initial conditions. Additionally, a Monte Carlo analysis showed the genetic-algorithm-tuned fuzzy controller tended to settle faster than the linear quadratic regulator over a variety of initial conditions.
- 作者:
- Cohen, Kelly; Putman, Philip T., and Walker, Alex R.
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/13/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2015-09
- 证书:
- All rights reserved
-
- Type:
- Image
- 摘抄:
- Comanthus alternans
- 作者:
- Meyer, David L.
- 提交者:
- David L. Meyer
- 上传日期:
- 02/13/2017
- 更改日期:
- 02/13/2017
- 创建:
- 2017-02-13
- 证书:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Article
- 摘抄:
- Fuzzy logic is used in a variety of applications because of its universal approximator attribute and non-linear characteristics. But, it takes a lot of trial and error to come up with a set of membership functions and rule-base that will effectively work for a specific application. This process could be simplified by using a heuristic search algorithm like Genetic Algorithm (GA). In this paper, genetic fuzzy is applied to the task assignment for cooperating Unmanned Aerial Vehicles (UAVs) classified as the polygon visiting multiple traveling salesman problem (PVMTSP). The PVMTSP finds a lot of applications including UAV swarm routing. We propose a method of genetic fuzzy clustering that would be specific to PVMTSP problems and hence more efficient compared to k-means and c-means clustering. We developed two different algorithms using genetic fuzzy. One evaluates the distance covered by each UAV to cluster the search-space and the other uses a cost function that approximates the distance covered thus resulting in a reduced computational time. We compare these two approaches to each other as well as to an already benchmarked fuzzy clustering algorithm which is the current state-of-the-art. We also discuss how well our algorithm scales for increasing number of targets. The results are compared for small and large polygon sizes.
- 作者:
- Cohen, Kelly; Ernest, Nicholas D., and Sathyan, Anoop
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/13/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2015-12
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- UAV’s are being increasingly used today than ever before in both military and civil applications. A certain level of autonomy is imperative to the future of UAV’s. A quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAV’s are VTOL and hovering capabilities as well as a greater maneuverability. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. The objective of this research endeavor is to present the steps of designing, building and simulating an intelligent flight control module for a quadrotor UAV. Validation of the math model developed is discussed using actual flight data. Excellent attitude tracking is demonstrated for near hover flight regimes. System design is comprehensively dealt with. The responses are analyzed and future work involving hardware-in-the-loop simulations is proposed.
- 作者:
- Cohen, Kelly and Sureshkumar, Vijaykumar
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/13/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2014-12
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- Wildfire is one of the most significant disturbances responsible for reshaping the terrain and changing the ecosystem of a particular region. Its detrimental effects on environment as well as human lives and properties, and growing trend in terms of frequency and intensity of wildfires over the last decade have necessitated the development of efficient forest fire management techniques. During the last three decades, Forest Fire Decision Support Systems (FFDSS) have been developed to help in the decision-making processes during forest fires by providing necessary information on fire detection, their status and behavior, and other aspects of forest fires. However, most of these decision support systems lack the capability of developing intelligent fire suppression strategies based upon current status and predicted behavior of forest fire. This paper presents an approach for development of efficient fireline building strategies via intelligent resource allocation. A Genetic Algorithm based approach has been proposed in this paper for resource allocation and optimum fireline building that minimizes the total damage due to wildland fires. The approach is based on a simulation–optimization technique in which the Genetic Algorithm uses advanced forest fire propagation models based upon Huygens principles for evaluation of cost index of its solutions. Both homogeneous and heterogeneous environmental conditions have been considered. Uncertainties in weather conditions as well as imperfect knowledge about exact vegetation and topographical conditions make exact prediction of wildfires very difficult. The paper incorporates Monte-Carlo simulations to develop robust strategies in uncertain conditions. Extensive simulations demonstrate the effectiveness of the proposed approach in efficient resource allocation for fighting complex wildfires in uncertain and dynamic conditions.
- 作者:
- Cohen, Kelly; Homchaudhuri, Baisravan, and Kumar, Manish
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/13/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2013-04
- 证书:
- All rights reserved