Cooperative Fault Diagnosis and Control of a Network of Unmanned Systems

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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.