Distributed Fault Detection in Formation of Multi-Agent Systems with Attack Impact Analysis

Autonomous Underwater Vehicles (AUVs) are capable of performing a variety of deepwater marine applications as in multiple mobile robots and cooperative robot reconnaissance. Due to the environment that AUVs operate in, fault detection and isolation as well as the formation control of AUVs are more challenging than other Multi-Agent Systems (MASs). In this thesis, two main challenges are tackled. We first investigate the formation control and fault accommodation algorithms for AUVs in presence of abnormal events such as faults and communication attacks in any of the team members. These undesirable events can prevent the entire team to achieve a safe, reliable, and efficient performance while executing underwater mission tasks. For instance, AUVs may face unexpected actuator/sensor faults and the communication between AUVs can be compromised, and consequently make the entire multi-agent system vulnerable to cyber-attacks. Moreover, a possible deception attack on network system may have a negative impact on the environment and more importantly the national security. Furthermore, there are certain requirements for speed, position or depth of the AUV team. For this reason, we propose a distributed fault detection scheme that is able to detect and isolate faults in AUVs while maintaining their formation under security constraints. The effects of faults and communication attacks with a control theoretical perspective will be studied. Another contribution of this thesis is to study a state estimation problem for a linear dynamical system in presence of a Bias Injection Attack (BIA). For this purpose, a Kalman Filter (KF) is used, where we show that the impact of an attack can be analyzed as the solution of a quadratically constrained problem for which the exact solution can be found efficiently. We also introduce a lower bound for the attack impact in terms of the number of compromised actuators and a combination of sensors and actuators. The theoretical findings are accompanied by simulation results and numerical can study examples

Cooperative Control and Fault Recovery for Network of Heterogeneous Autonomous Underwater Vehicles

The purpose of this thesis is to develop cooperative recovery control schemes for a team of heterogeneous autonomous underwater vehicles (AUV). The objective is to have the network of autonomous underwater vehicles follow a desired trajectory while agents maintain a desired formation. It is assumed that the model parameters associated with each vehicle is different although the order of the vehicles are the same. Three cooperative control schemes based on dynamic surface control (DSC) technique are developed. First, a DSC-based centralized scheme is presented in which there is a central controller that has access to information of all agents at the same time and designs the optimal solution for this cooperative problem. This scheme is used as a benchmark to evaluate the performance of other schemes developed in this thesis. Second, a DSC-based decentralized scheme is presented in which each agent designs its controller based on only its information and the information of its desired trajectory. In this scheme, there is no information exchange among the agents in the team. This scheme is also developed for the purpose of comparative studies. Third, two different semi-decentralized or distributed schemes for the network of heterogeneous autonomous underwater vehicles are proposed. These schemes are a synthesis of a consensus-based algorithm and the dynamic surface control technique with the difference that in one of them the desired trajectories of agents are used in the consensus algorithm while in the other the actual states of the agents are used. In the former scheme, the agents communicate their desired relative distances with the agents within their set of nearest neighbors and each agent determines its own control trajectory. In this semi-decentralized scheme, the velocity measurements of the virtual leader and all the followers are not required to reach the consensus formation. However, in the latter, agents communicate their relative distances and velocities with the agents within their set of nearest neighbors. In both semi-decentralized schemes only a subset of agents has access to information of a virtual leader. The comparative studies between these two semi-decentralized schemes are provided which show the superiority of the former semi-decentralized scheme over latter. Furthermore, to evaluate the efficiency of the proposed DSC-based semi-decentralized scheme with consensus algorithm using desired trajectories, a comparative study is performed between this scheme and three cooperative schemes of model-dependent coordinated tracking algorithm, namely the centralized, decentralized, and semi-decentralized schemes. Given that the dynamics of autonomous underwater vehicles are inevitably subjected to system faults, and in particular the actuator faults, to improve the performance of the network of agents, active fault-tolerant control strategies corresponding to the three developed schemes are also designed to recover the team from the loss-of-effectiveness in the actuators and to ensure that the closed-loop signals remain bounded and the team of heterogeneous autonomous underwater vehicles satisfy the overall design specifications and requirements. The results of this research can potentially be used in various marine applications such as underwater oil and gas pipeline inspection and repairing, monitoring oil and gas pipelines, detecting and preventing any oil and gas leakages. However, the applications of the proposed cooperative control and its fault-tolerant scheme are not limited to underwater formation path-tracking and can be applied to any other multi-vehicle systems that are characterized by Euler–Lagrange equations

Service-oriented agent architecture for autonomous maritime vehicles

Advanced ocean systems are increasing their capabilities and the degree of autonomy more and more in order to perform more sophisticated maritime missions. Remotely operated vehicles are no longer cost-effective since they are limited by economic support costs, and the presence and skills of the human operator. Alternatively, autonomous surface and underwater vehicles have the potential to operate with greatly reduced overhead costs and level of operator intervention. This Thesis proposes an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. They are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The architectural foundation to achieve the ICA lays on the flexibility of service-oriented computing and agent technology. An ontological database captures the operator skills, platform capabilities and, changes in the environment. The information captured, stored as knowledge, enables reasoning agents to plan missions based on the current situation. The ICA implementation is verified in simulation, and validated in trials by means of a team of autonomous marine robots. This Thesis also presents architectural details and evaluation scenarios of the ICA, results of simulations and trials from different maritime operations, and future research directions

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics