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Aerospace Engineering and Engineering Mechanics
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- Type:
- Article
- 摘抄:
- The present study deals with an AFCA (Adaptive Fuzzy Control Algorithm) for an Euler-Bemoulli approximation of a two-dimensional version of a cantilever beam-like orthogonal tetrahedral space truss. Transient disturbances, modeled as a unit impulse, excite all the modes of the beam. The resulting transverse displacement at the free end of the beam and its corresponding rate are observed by sensors placed there, and active control of the beam is provided by a collocated force actuator. A design methodology, based on fuzzy logic which assumes no a priori knowledge of plant dynamics, for the closed-loop control algorithm results in relatively quick settling times, low overshoots and dying out of vibration within a few seconds. The control algorithm is enhanced and made much faster by eliminating the need of repeatedly solving the set of differential equations of motion of an emulated dynamic vibration absorber. When the control force is turned off after a mere 15 seconds, almost all the vibrational energy is dissipated as the beam returns to its undisturbed state throughout its length. In addition, the performance of the AFCA is insensitive to varying initial conditions. To examine the robustness of the control system to changes in the temporal dynamics of the cantilever beam, the transient disturbance response to a considerably perturbed plant is simulated. The Young's modulus of the beam was raised as well as lowered by 60%, substantially perturbing the natural frequencies of vibration compared to the nominal plant. The AFCA provided similar settling times and rates of vibrational energy dissipation, satisfying the aim of plant model independence.
- 作者:
- Abramovich, Haim; Weller, Tanchum; Cohen, Kelly, and Levitas, Joseph
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/08/2017
- 更改日期:
- 04/05/2017
- 创建:
- 1996-03
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- For a Timoshenko beam model the equations of motion, representing the anisotropic continuum model of a two-dimensional, latticed, large space structure, are extended to include coupling between the extensional, shear and bending modes. This analytical model, applied to a 20-bay, orthogonal, tetrahedral, cantilevered truss structure, is used to determine the transient response when subjected to a unit impulse. It is demonstrated that for beam-like structures having a fixed bending stiffness and beam mass an increase in diagonal stiffness, on account of the stiffness of the vertical girder, leads to a rise in the transverse shear rigidity. This results in higher natural frequencies and a reduction in peak displacement. In addition, in an asymmetrical truss configuration, coupling between the extensional and shear modes raises the maximum peak displacement compared to that obtained for a symmetric truss. The model is modified to investigate the introduction of passive damping in the form of several dynamic vibration absorbers. For a fixed absorber mass budget, a simple yet efficient absorber parameter optimization procedure, based on the classical steady state criteria of a 2-DOF system, is developed to design several absorbers each tuned to a different modal frequency. It is found that inclusion of transverse shear rigidity, as a design parameter in damping augmentation studies, reduces settling time for predetermined maximum peak displacements.
- 作者:
- Weller, T. and Cohen, Kelly
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/08/2017
- 更改日期:
- 04/05/2017
- 创建:
- 1994-08
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- Breakthroughs in genetic fuzzy systems, most notably the development of the Genetic Fuzzy Tree methodology, have allowed fuzzy logic based Artificial Intelligences to be developed that can be applied to incredibly complex problems. The ability to have extreme performance and computational efficiency as well as to be robust to uncertainties and randomness, adaptable to changing scenarios, verified and validated to follow safety specifications and operating doctrines via formal methods, and easily designed and implemented are just some of the strengths that this type of control brings. Within this white paper, the authors introduce ALPHA, an Artificial Intelligence that controls flights of Unmanned Combat Aerial Vehicles in aerial combat missions within an extreme-fidelity simulation environment. To this day, this represents the most complex application of a fuzzy-logic based Artificial Intelligence to an Unmanned Combat Aerial Vehicle control problem. While development is on-going, the version of ALPHA presented withinwas assessed by Colonel (retired)Gene Lee who described ALPHA as “the most aggressive, responsive, dynamic and credible AI (he’s) seen-to-date.” The quality of these preliminary results in a problem that is not only complex and rife with uncertainties but also contains an intelligent and unrestricted hostile force has significant implications for this type of Artificial Intelligence. This work adds immensely to the body of evidence that this methodology is an ideal solution to a very wide array of problems.
- 作者:
- Schumacher, Corey; Cohen, Kelly; Ernest, Nicholas; Carroll, David; Lee, Gene, and Clark, Matthew
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/08/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2016-03
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire 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 deploy ability.
- 作者:
- Sharma, Balaji R.; Cohen, Kelly, and Kumar, Manish
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/08/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2013-10
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- The methods and outcome of a senior undergraduate project related to the control of a turbulent cylinder wake flow using plasma actuators are summarized in this article. The study integrates computational fluid dynamics (CFD) with experimentation and combines fluid mechanics with flow control research, crossing the boundaries between engineering disciplines.Comput. Appl. Eng. Educ.
- 作者:
- Cohen, Kelly; McLaughlin, Thomas; Seaver, Christopher A., and Aradag, Selin
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/08/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2009-02
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- Comparison of approximate approaches to solving the Travelling Salesman Problem and its application to UAV swarming. International Journal of Unmanned Systems Engineering. 3(1): 1-16. The Travelling Salesman Problem (TSP) is a widely researched Non-deterministic Polynomial-time hard optimization problem with a range of important applications in a wide spectrum of disciplines including aerospace engineering. In this paper, a comparison of different approaches to solve the TSP and also its application towards swarming of UAVs is considered. The objective of the TSP is to determine the optimal route associated with the shortest tour connecting all targets just once. Genetic Algorithms (GA) are one of the most widely applied techniques for solving this class of optimization problems. Two other techniques, 2-opt and Particle Swarm Optimization, are used and the results are compared with those obtained using GA. The comparison is made for different numbers of targets, using salient figures of merit such as computational time required and the cost function which is the minimum solution (distance) obtained. Results show that the 2-opt approach with the closest neighbour as initial starting point for the search yields superior performance. In the Multiple Travelling Salesman Problem, we propose a cluster-first approach which allocates each specific UAV to a subset of targets. The 200 targets are divided into four clusters corresponding to the four UAVs and then TSP algorithms like 2-opt and GA are employed to solve each cluster. This approach drastically reduces the computational time and also gives much better results than the conventional technique of directly applying GA over the 200 targets.
- 作者:
- Cohen, Kelly; Boone, Nathan, and Sathyan, Anoop
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/03/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2015-01
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- Not Available
- 作者:
- Cohen, Kelly and Ernest, Nick
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/03/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2015-12
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- 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.
- 作者:
- Schumacher, Corey; Cohen, Kelly; Ernest, Nicholas; Casbeer, David, and Kivelevitch, Elad
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/03/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2015-05
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- 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.
- 作者:
- Sharma, Balaji R.; Cohen, Kelly, and Kumar, Manish
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/03/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2013-10
- 证书:
- All rights reserved
-
- Type:
- Article
- 摘抄:
- 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.
- 作者:
- Manish, Kumar; Cohen, Kelly, and HomChaudhuri, Baisravan
- 提交者:
- Kelly Cohen
- 上传日期:
- 02/03/2017
- 更改日期:
- 04/05/2017
- 创建:
- 2010-07
- 证书:
- All rights reserved