Cooperative Fault Diagnosis and Control of a Network of Unmanned Systems

控制、计算和通信领域的最新技术进步引起了人们对开发新一代高度互联、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，例如用于情报、监视和侦察(ISR)、自然灾害和环境监测、科学地球和外层空间观测和发现的无人驾驶飞行器(如无人驾驶飞行器、无人水下飞行器和无人地面飞行器(UAV/UUV/UGV)、卫星和空间飞行器(SVS))的协作团队。由于执行器和传感器的异常和故障等不良影响，无人系统协作团队(UMS)的健康状况必须得到监控，以便这些所谓的“代理”能够诊断故障，响应和重新配置控制律(控制恢复和可重构)，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。因此，有必要协作性地调整控制律，以使代理从异常、故障和故障的影响中恢复过来。具体地说，需要开发自主智能的分布式故障诊断(FD)和故障重构(FR)控制系统来管理UMS/SVS的网络化团队。特别是，如果任何一个智能体发生故障，团队没有配备自主容错控制能力，团队的稳定性、共识和队形可能不再保持，这可能导致整个团队的不稳定。拟议研究的主旨是将FD&R技术和方法从单一的无人系统推广到一组合作的UMS/SVS团队，以完成给定的任务。故障诊断和恢复(FD&R)技术已被研究并适用于单个移动机器人系统，但对于UMS/SVS团队来说，故障诊断和恢复技术并不常见和广泛研究并可用，这是本方案的主要区别和独到之处。该研究的目的是为自主车载系统提供增强的能力，以确定UMS/SVS相互作用的网络的协同故障诊断和控制的最有效分配、配置、策略、算法和体系结构。自主展示新颖集体行为的UMS/SVS自组织和自适应网络的设计和开发提供了几个目前利用单个代理无法获得或可能获得的优势和机会。本项目设想和提出的基本挑战和问题是，为管理和确定合作的UMS/SVS团队之间的数据、知识和行动的交换，开发新的、正式的、严格的分布式和半分散的方法。这些目标将通过利用受通信网络和计算资源限制的控制方案来实现，用于协作故障诊断、协作恢复和重新配置控制目标，以保证和维持任务要求。提出的创新研究方法是利用决策理论、非线性鲁棒和自适应、协作性和协作性的分布式故障诊断和控制技术。这项研究将为加拿大政府实验室和整个行业特别是航空航天行业非常感兴趣的极其重要的实际问题提供严格的解决方案，并将积累人力资本并发展可持续的研究能力。

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.