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survivability: a hierarchical fuzzy logic layered model for Threat Management of Unmanned Ground Vehicles

机译：生存能力：一种用于无人机地面车辆威胁管理的分层模糊逻辑分层模型

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Survivability has always been of interest in the defense of any armored vehicles. There has been many reports and papers on the survivability of U.S. Army ground vehicles. A Survivability severity model can be best described as the analogy to the layers of an onion, in which each layer of onion describes a different severity level and the phase of threat detected and severity to apply countermeasures. The objective of this paper is to suggest an evaluation tool that contains an algorithm and procedure for the reliability of manned and unmanned ground vehicles. A decision-making system is proposing for the theoretical survivability and is calculated from a threat level in the form of severity. A generic framework algorithm, consists of both linear and non-linear vehicle dynamics systems, and is included in this paper, which consists of the Fuzzy approach and various scenarios, based on straight path projection. Further, to increase the level of rigor, a layered fuzzy control system using various vehicle dynamics parameters [1] and a methodology for designing an adaptive hierarchical fuzzy model [2] and to accommodate various system parameters dependencies, are describing in this paper as a part of the survivability model. It is hoped that different users will tailor this evaluation tool and used extensively by various research workers working in different area. Several probabilistic cases were included in this paper and implemented by converting to linguistic fuzzy parameters to evaluate the algorithm. A simulation model is designed using supervisory fuzzy rule set and several simulation studies have been done which illustrate the effectiveness of the given approach. The result is a robust d flexible control system.
机译：生存能力始终是对任何装甲车的辩护感兴趣。有许多关于美国陆军地面车辆的存活率的报告和论文。生存性严重程度模型可以最好地描述为对洋葱的层的类比，其中每层洋葱描述不同的严重性水平和检测到的威胁阶段和施加对策的严重性。本文的目的是建议一种评估工具，该工具包含载人和无人机的可靠性的算法和程序。决策系统提出了理论生存能力，并且由严重程度的形式从威胁水平计算。通用框架算法包括线性和非线性车辆动力学系统，并包括在本文中，该纸张包括基于直路投影的模糊方法和各种场景。此外，为了增加利却的水平，使用各种车辆动力学参数[1]的分层模糊控制系统和用于设计自适应分层模糊模型[2]的方法，并适应各种系统参数依赖性，正在描述本文作为一个一部分存活性模型。希望不同的用户将根据在不同地区工作的各种研究工作人员广泛使用这种评估工具。本文中包含了几种概率案例，并通过转换为语言模糊参数来实现以评估算法。使用监控模糊规则集设计模拟模型，并进行了几项模拟研究，其说明了给定方法的有效性。结果是强大的D柔性控制系统。

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