Cooperative Fault Diagnosis and Control of a Network of Unmanned Systems

无人系统网络的协同故障诊断与控制

• 批准号: RGPIN-2014-04265
• 负责人: Khorasani, Khashayar
• 金额: $ 4.44万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637406
• 关键词: Cooperative; Fault; Diagnosis; Control; Network

Recent technological advances in control, computing, and communications have generated intense interest in development of a new generation of highly interconnected, distributed, sensor rich autonomous systems for applications in a variety of complex settings such as cooperating team of unmanned vehicles (such as unmanned aerial, unmanned underwater, and unmanned ground vehicles (UAVs/UUVs/UGVs), satellites, and space vehicles (SVs)) for intelligence, surveillance, and reconnaissance (ISR), natural disaster and environmental monitoring, scientific Earth and outer space observations and discovery, to name a few. Due to undesirable effects such as anomalies and faults in actuators and sensors, the health of cooperating team of unmanned systems (UMS) must be monitored so that these so-called “agents” can diagnose faults, respond and reconfigure control laws (control recovery and reconfigurability), reach a consensus, and propose a course of action to unforeseen and unpredictable circumstances. Consequently, it will be necessary to cooperatively adjust control laws to recover the agents from the effects of anomalies, faults, and failures. Specifically, what is required is to develop autonomous and intelligent distributed fault diagnosis (FD) and fault reconfiguration (FR) control systems to manage the networked team of UMS/SVs. In particular, if any agent is subjected to a fault and the team is not equipped with autonomous fault tolerant control capabilities, the stability, consensus, and formation of the team may no longer be maintained and this could lead to instability of the entire team. The main thrust of the proposed research is to generalize and extend FD&R techniques and methodologies from a single unmanned system to a team of cooperating UMS/SVs tasked to accomplish a given mission. Fault diagnosis and recovery (FD&R) techniques have been studied and are available for individual mobile robotic systems, however, FD&R techniques are not common and extensively researched and available for a team of UMS/SVs, which is the main distinguishing aspect and uniqueness of this proposal. The objectives of the proposed research are to provide enhanced capabilities for autonomous on-board systems in determining the most efficient allocation, configuration, strategies, algorithms, and architectures for cooperative fault diagnosis and control of a network of interacting UMS/SVs. Design and development of a self-organizing and adaptive network of UMS/SVs that autonomously demonstrate novel collective behaviors offer several advantages and opportunities that are not currently available or possible by utilizing a single agent. The fundamental challenges and issues that are envisaged and proposed in this project are development of novel, formal, and rigorous distributed and semi-decentralized methodologies for management and determination of exchange of data, knowledge, and actions among the team of cooperating UMS/SVs. These goals are to be accomplished by utilizing control schemes that are constrained by the communication network and computational resources for cooperative fault diagnosis, cooperative recovery and reconfiguration control objectives for guaranteeing and maintaining the mission requirements. The proposed innovative research methodologies envisaged are to utilize decision theoretic, nonlinear robust and adaptive, collaborative and cooperative distributed fault diagnosis and control techniques. This research will provide rigorous solutions to practical problems of paramount importance that are of significant interest to Canadian government laboratories and industry in general and to the aerospace industry in particular, and will accumulate human capital and develop sustainable research capabilities.

最近在控制、计算和通信方面的技术进步引起了人们对开发新一代高度互连、分布式、传感器丰富的自主系统的浓厚兴趣，这些系统适用于各种复杂的环境，例如无人驾驶车辆的合作团队（例如无人机） 、无人水下和无人地面车辆（UAV/UUV/UGV）、卫星和航天器（SV）），用于情报、监视和侦察（ISR）、自然灾害和环境监测、科学地球举几例来说，由于执行器和传感器的异常和故障等不良影响，必须对无人系统（UMS）合作团队的健康状况进行监控，以便这些所谓的“代理”能够正常工作。诊断故障、响应和重新配置控制法则（控制恢复和可重构性）、达成共识，并针对不可预见和不可预测的情况提出行动方案。具体来说，需要开发自主且智能的分布式故障诊断（FD）和故障重新配置（FR）控制系统来管理 UMS/SV 的网络化团队。任何一个智能体出现故障，并且团队不具备自主容错控制能力，团队的稳定性、共识和形成可能不再得以维持，这可能会导致整个团队的推力不稳定。研究的目的是将 FD&R 技术和方法从单个无人系统推广到负责完成给定任务的协作 UMS/SV 团队，故障诊断和恢复 (FD&R) 技术已被研究并可用于单个移动机器人系统。技术对于 UMS/SV 团队来说并不常见，也没有被广泛研究和使用，这是该提案的主要区别和独特之处。拟议研究的目标是为自主机载提供增强的功能。系统确定最有效的分配、配置、策略、算法和架构，以进行交互的 UMS/SV 网络的协作故障诊断和控制 设计和开发 UMS/SV 的自组织和自适应网络，该网络能够自主地展示新颖性。集体行为提供了目前使用单个代理无法获得或不可能的多种优势和机会。该项目设想和提出的基本挑战和问题是开发新颖的、正式的、严格的分布式和半分散的管理方法。和交换的决定这些目标将通过利用受通信网络和计算资源约束的方案进行控制来实现，以实现协作故障诊断、协作恢复和重新配置控制目标，以保证和维护。所提出的创新研究方法是利用决策理论、非线性稳健和自适应、协作和协作的分布式故障诊断和控制技术，这项研究将为加拿大感兴趣的最重要的实际问题提供严格的解决方案。政府实验室整个行业，特别是航空航天业，并将积累人力资本并发展可持续的研究能力。