Autonomous, intelligent, and distributed diagnosis, prognosis, and health management (DPHM) and cooperative control for a communicating networked team of unmanned systems (UMS)

无人系统 (UMS) 通信网络团队的自主、智能、分布式诊断、预后和健康管理 (DPHM) 以及协作控制

• 批准号: 356636-2007
• 负责人: Khorasani, Khashayar
• 金额: $ 7.28万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects Supplemental Competition
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=403033
• 关键词: Autonomous; intelligent; distributed; diagnosis; prognosis

The proposed communicating networked team of unmanned systems (UMS) consisits of a large number of deployed satellites, unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), and unattended ground sensors (UGSs). The goals and objectives of the research investigated in this application are to provide enhanced capabilities and support system to ground operators in determining the most efficient and optimal allocation, configuration, architectures, and control for the unmanned assets to autonomously and intelligently respond to environmental uncertainties for achieving the evolving mission requirements. Design and development of self-organizing and intelligent unmanned networks composed of individual autonomous/semi-autonomous agents that demonstrate complex collective behaviors offer several novel advantages and opportunities that are not currently demonstrated and possible. The agents in UMS should adapt their strategies hi response to actions by others or due to anamolies, faults, and failures in sensors, actuators, and components of the UMS assets and should quickly cope with environmental, terrain and mission objective changes. The proposed overall novel modeling, analysis, and design techniques developed here are envisaged to utilize rigorous mathematical model-based decision theoretic algorithms, nonlinear robust and adaptive techniques, collaborative and cooperative distributed control, and computationally intelligent algorithms. By utilizing the overall software architectures developed in this project, the operators involved in planning, scheduling, task allocation and management of UMS assets are empowered with decision making tools and support systems to generate rules and procedures for an effective execution and response to adversarial threats as well as faults and failures. The proposed innovative solutions should lead to enhanced mission performance through minimizing and optimizing communication exchanges with support and guidance from ground managers and are made feasible by ensuring that the UMS agents are able to "think" for them-selves, and act in novel ways to ensure they carry out the goals of the mission.

拟议的无人系统（UMS）通信网络团队由大量部署的卫星、无人地面车辆（UGV）、无人机（UAV）和无人值守地面传感器（UGS）组成。本应用研究的目的和目标是为地面操作员提供增强的功能和支持系统，以确定无人资产的最有效和最佳的分配、配置、架构和控制，以自主、智能地响应环境不确定性满足不断变化的任务要求。由表现出复杂集体行为的个体自​​主/半自主代理组成的自组织和智能无人网络的设计和开发提供了目前尚未证明和不可能的一些新颖的优势和机会。 UMS 中的代理应根据其他人的行为或由于 UMS 资产的传感器、执行器和组件的异常、故障和故障而调整其策略，并应快速应对环境、地形和任务目标的变化。这里开发的整体新颖的建模、分析和设计技术设想利用严格的基于数学模型的决策理论算法、非线性鲁棒和自适应技术、协作和协作分布式控制以及计算智能算法。通过利用该项目中开发的整体软件架构，参与 UMS 资产的规划、调度、任务分配和管理的操作人员能够获得决策工具和支持系统，以生成规则和程序，以便有效执行和响应敌对威胁：以及错误和失败。所提出的创新解决方案应在地面管理人员的支持和指导下，通过最小化和优化通信交流来提高任务绩效，并通过确保 UMS 特工能够独立“思考”并以新颖的方式采取行动来实现任务绩效。确保他们实现使命目标。