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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=655477
• 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.

最新的技术进步在控制，计算和通信方面取得了进步，引起了新一代高度互连，分布式，传感器丰富的自主自主系统在各种复杂环境中的应用，例如合作无人驾驶的车辆（例如无人驾驶的，无人驾驶的，无人驾驶的水下和无人驾驶的地面车辆）（Uavs/ugvs fors and uivs/ugvs），satells/ugvs and ubvs and sate and sate and sate and sate and ugvs and sate）情报，监视和侦察（ISR），自然灾害和环境监测，科学地球和外层空间的观察和发现，仅举几例。由于执行器和传感器中的异常和故障等不良效果，必须监视无人系统（UMS）的合作团队的健康状况，以使这些所谓的“代理”可以诊断出缺陷，响应和重新配置控制法律（控制恢复和重新配置），并提出共识，并提出同意的过程，并提出对统一的行动，并有能力进行操作，并有效地不得不纠正。因此，有必要合作调整控制法律以从异常，故障和失败的影响中恢复代理。具体而言，需要的是开发自主和智能的分布式故障诊断（FD）和故障重新配置（FR）控制系统，以管理UMS/SVS的网络团队。特别是，如果任何代理商遭受过失，并且团队不具备自主容忍控制能力，则可能不再保持团队的稳定性，共识和成立，这可能会导致整个团队的不稳定。拟议的研究的主要目的是将FD＆R技术和方法从单个无人系统的系统概括和扩展到一个合作的UMS/SVS团队，该团队负责完成给定的任务。已经研究了故障诊断和恢复（FD＆R）技术，并适用于单个移动机器人系统，但是，FD＆R技术并不常见，并且对UMS/SVS的团队进行了广泛的研究，这是该建议的主要区别和独特性。拟议的研究的目标是为自动板上系统提供增强的功能，以确定最有效的分配，配置，策略，算法和体系结构，以进行合作故障诊断和控制UMS/SVS网络的合作故障诊断和控制。自主展示新型集体行为的UMS/SV的自组织和自适应网络的设计和开发提供了几种优势和机会，这些优点和机会通过使用单个代理而当前无法获得或可能。该项目中设想和提出的基本挑战和问题是开发新颖，正式和严格的分布式和半排斥的方法，用于管理和确定合作UMS/SVS团队之间的数据，知识和行动的交换。这些目标应通过利用受通信网络和计算资源约束的控制方案来实现，以进行合作故障诊断，合作恢复和重新配置控制目标，以保证和维护任务要求。所提出的创新研究方法是利用决策理论，非线性鲁棒和适应性，协作和合作分布式的故障诊断和控制技术。这项研究将为最重要的问题提供严格的解决方案，这对加拿大政府实验室和行业尤其是航空航天行业具有重要意义，并将积累人力资本并发展可持续的研究能力。