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

Neural Network Observer-Based Prescribed-Time Fault-Tolerant Tracking Control for Heterogeneous Multiagent Systems With a Leader of Unknown Disturbances

This study investigates the prescribed-time leader-follower formation strategy for heterogeneous multiagent sys-tems including unmanned aerial vehicles and unmanned ground vehicles under time-varying actuator faults and unknown dis-turbances based on adaptive neural network observers and backstepping method. Compared with the relevant works, the matching and mismatched disturbances of the leader agent are further taken into account in this study. A distributed fixed-time observer is developed for follower agents in order to timely obtain the position and velocity states of the leader, in which neural networks are employed to approximate the unknown disturbances. Furthermore, the actual sensor limitations make each follower only affected by local information and measurable local states. As a result, another fixed-time neural network observer is proposed to obtain the unknown states and the complex uncertainties. Then, a backstepping prescribed-time fault-tolerant formation controller is constructed by utilizing the estimations, which not only guarantees that the multiagent systems realize the desired formation configuration in a user-assignable finite time, but also ensures that the control action can be smooth everywhere. Finally, simulation examples are designed to testify the validity of the developed theoretical method

COOPERATIVE AND CONSENSUS-BASED CONTROL FOR A TEAM OF MULTI-AGENT SYSTEMS

Cooperative control has attracted a noticeable interest in control systems community due to its numerous applications in areas such as formation flying of unmanned aerial vehicles, cooperative attitude control of spacecraft, rendezvous of mobile robots, unmanned underwater vehicles, traffic control, data network congestion control and routing. Generally, in any cooperative control of multi-agent systems one can find a set of locally sensed information, a communication network with limited bandwidth, a decision making algorithm, and a distributed computational capability. The ultimate goal of cooperative systems is to achieve consensus or synchronization throughout the team members while meeting all communication and computational constraints. The consensus problem involves convergence of outputs or states of all agents to a common value and it is more challenging when the agents are subjected to disturbances, measurement noise, model uncertainties or they are faulty. This dissertation deals with the above mentioned challenges and has developed methods to design distributed cooperative control and fault recovery strategies in multi-agent systems. Towards this end, we first proposed a transformation for Linear Time Invariant (LTI) multi-agent systems that facilitates a systematic control design procedure and make it possible to use powerful Lyapunov stability analysis tool to guarantee its consensus achievement. Moreover, Lyapunov stability analysis techniques for switched systems are investigated and a novel method is introduced which is well suited for designing consensus algorithms for switching topology multi-agent systems. This method also makes it possible to deal with disturbances with limited root mean square (RMS) intensities. In order to decrease controller design complexity, a iii method is presented which uses algebraic connectivity of the communication network to decouple augmented dynamics of the team into lower dimensional parts, which allows one to design the consensus algorithm based on the solution to an algebraic Riccati equation with the same order as that of agent. Although our proposed decoupling method is a powerful approach to reduce the complexity of the controller design, it is possible to apply classical pole placement methods to the transformed dynamics of the team to develop and obtain controller gains. The effects of actuator faults in consensus achievement of multi-agent systems is investigated. We proposed a framework to quantitatively study actuator loss-of-effectiveness effects in multi-agent systems. A fault index is defined based on information on fault severities of agents and communication network topology, and sufficient conditions for consensus achievement of the team are derived. It is shown that the stability of the cooperative controller is linked to the fault index. An optimization problem is formulated to minimize the team fault index that leads to improvements in the performance of the team. A numerical optimization algorithm is used to obtain the solutions to the optimal problem and based on the solutions a fault recovery strategy is proposed for both actuator saturation and loss-of-effectiveness fault types. Finally, to make our proposed methodology more suitable for real life scenarios, the consensus achievement of a multi-agent team in presence of measurement noise and model uncertainties is investigated. Towards this end, first a team of LTI agents with measurement noise is considered and an observer based consensus algorithm is proposed and shown that the team can achieve H∞ output consensus in presence of both bounded RMS disturbance input and measurement noise. In the next step a multi-agent team with both linear and Lipschitz nonlinearity uncertainties is studied and a cooperative control algorithm is developed. An observer based approach is also developed to tackle consensus achievement problem in presence of both measurement noise and model uncertainties

Fault-tolerant Synchronization of Autonomous Underwater Vehicles

The main objective of this thesis is to develop a fault-tolerant and reconfigurable synchronization scheme based on model-based control protocols for stern and sail hydroplanes that are employed as actuators in the attitude control subsystem (ACS) of an autonomous underwater vehicle (AUV). In this thesis two control approaches are considered for synchronization, namely i) state feedback synchronization, and ii) output feedback synchronization. Both problems are tackled by proposing a passive control approach as well as an active reconfiguration (re-designing the control gains). For the ”state feedback” synchronization scheme, to achieve consensus the relative/absolute measurements of the AUV’s states (position and attitude) are available. The states of a longitudinal model of an AUV are mainly heave, pitch, and their associated rates. For the state feedback problem we employ a static protocol, and it is shown that the multi-agent system will synchronize in the stochastic mean square sense in the presence of measurement noise. However, the resulting performance index defined as the accumulated sum of variations of control inputs and synchronization errors is high. To deal with this problem, Kalman filtering is used for states estimation that are used in synchronization protocol. Moreover, the e�ffects of parameter uncertainty of the agent’s dynamics are also investigated through simulation results. By employing the static protocol it is demonstrated that when a loss of e�ffectiveness (LOE) or float fault occurs the synchronization can still be achieved under some conditions. Finally, one of the main problems that is tackled in the state feedback scenario is our proposed proportional-integral (PI) control methodology to deal with the lock in place (LIP) fault. It is shown that if the LIP fault occurs, by employing a PI protocol the synchronization could still be achieved. Finally, our proposed dynamic synchronization protocol methodology is applied given that the fault (LOE/float) severity is known. Since after a fault occurrence the agents become heterogeneous, employing the dynamic scheme makes the task of reconfiguration (redesigning the gains) more e�ffective. For the ”output feedback” synchronization approach, to achieve consensus relative/absolute measurements of the AUV’s states except the pitch rate are available. For the output feedback problem a dynamic protocol through a Luenberger observer is first employed for state estimation and the synchronization achievement is demonstrated. Then, a system under state and measurement noise is considered, and it is shown that by employing a Kalman filter for the state estimation; the multi-agent system will synchronize in the stochastic mean square sense. Furthermore, by employing the static protocol, it is shown that when a LOE/float fault occurs the synchronization is still achieved under certain conditions. Finally, one of the main problems that is tackled in the output feedback scenario is our proposed dynamic controller methodology. The results of this scheme are compared with another approach that exploits both dynamic controller and dynamic observer. The former approach has less computational e�ort and results in more a robust control with respect to the actuator fault. The reason is that the later method employs an observer that uses the control input matrix information. When fault occurs, this information will not be correct any more. However, if there is a need to redesign the synchronization gains under faulty scenario, the later methodology is preferred. The reason is that the former approach becomes complicated when there is a fault even though its severity is known. In this thesis, fault-tolerant synchronization of autonomous underwater vehicles is considered. In the first chapter a brief introduction on the motivation, problem definition, objectives and the methodologies that are used in the dissertation are discussed. A literature review on research dedicated to synchronization, fault diagnosis, and fault-tolerant control is provided. In Chapter 2, a through literature review on unmanned underwater vehicles is covered. It also comprises a comprehensive background information and definitions including algebraic graph theory, matrix theory, and fault modeling. In the problem statement, the two main problems in this thesis, namely state feedback synchronization and output feedback synchronization are discussed. Chapters 3 and 4 will cover these two problems, their solutions, and the corresponding simulation results that are provided. Finally, Chapter 5 includes a discussion of conclusions and future work

Distributed Collision-Free Bearing Coordination of Multi-UAV Systems With Actuator Faults and Time Delays

Coordination of unmanned aerial vehicle (UAV) systems has received great attention from robotics and control communities. In this paper, we investigate the distributed formation tracking problem in heterogeneous nonlinear multi-UAV networks via bearing measurements. Firstly, a novel bearing-only protocol is designed for follower agents to achieve the desired formation. Particularly, we establish a compensation function on the basis of bearing measurements to deal with the non-linearity and actuator faults in the agent dynamics. The stability of the proposed strategy can be ensured by Lyapunov method in the presence of certain time delays. Moreover, to ensure safe operation in real-world scenarios, we extend the protocol and propose a sufficient condition to avoid potential collisions among the agents. The robustness of the collision-free controller with continuous action is also considered in the protocol design. Finally, the simulation case studies are presented to validate the feasibility of the theoretical results

Distributed adaptive fault-tolerant leader-following formation control of nonlinear uncertain second-order multi-agent systems

This paper presents a distributed integrated fault diagnosis and accommodation scheme for leader‐following formation control of a class of nonlinear uncertain second‐order multi‐agent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The time‐varying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault‐tolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closed‐loop stability and asymptotic convergence properties of the leader‐follower formation are rigorously established under different modes of the fault‐tolerant control system

Cooperative control of a network of multi-vehicle unmanned systems

Development of unmanned systems network is currently among one of the most important areas of activity and research with implications in variety of disciplines, such as communications, controls, and multi-vehicle systems. The main motivation for this interest can be traced back to practical applications wherein direct human involvement may not be possible due to environmental hazards or the extraordinary complexity of the tasks. This thesis seeks to develop, design, and analyze techniques and solutions that would ensure and guarantee the fundamental stringent requirements that are envisaged for these dynamical networks. In this thesis, the problem of team cooperation is solved by using synthesis-based approaches. The consensus problem is defined and solved for a team of agents having a general linear dynamical model. Stability of the team is guaranteed by using modified consensus algorithms that are achieved by minimizing a set of individual cost functions. An alternative approach for obtaining an optimal consensus algorithm is obtained by invoking a state decomposition methodology and by transforming the consensus seeking problem into a stabilization problem. In another methodology, the game theory approach is used to formulate the consensus seeking problem in a "more" cooperative framework. For this purpose, a team cost function is defined and a min-max problem is solved to obtain a cooperative optimal solution. It is shown that the results obtained yield lower cost values when compared to those obtained by using the optimal control technique. In game theory and optimal control approaches that are developed based on state decomposition, linear matrix inequalities are used to impose simultaneously the decentralized nature of the problem as well as the consensus constraints on the designed controllers. Moreover, performance and stability properties of the designed cooperative team is analyzed in presence of actuator anomalies corresponding to three types of faults. Steady state behavior of the team members are analyzed under faulty scenarios. Adaptability of the team members to the above unanticipated circumstances is demonstrated and verified. Finally, the assumption of having a fixed and undirected network topology is relaxed to address and solve a more realistic and practical situation. It is shown that the stability and consensus achievement of the network with a switching structure and leader assignment can still be achieved. Moreover, by introducing additional criteria, the desirable performance specifications of the team can still be ensured and guaranteed

Distributed Adaptive Fault-Tolerant Control of Uncertain Multi-Agent Systems

This paper presents an adaptive fault-tolerant control (FTC) scheme for a class of nonlinear uncertain multi-agent systems. A local FTC scheme is designed for each agent using local measurements and suitable information exchanged between neighboring agents. Each local FTC scheme consists of a fault diagnosis module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault-tolerant controllers activated after fault detection and after fault isolation, respectively. Under certain assumptions, the closed-loop system's stability and leader-follower consensus properties are rigorously established under different modes of the FTC system, including the time-period before possible fault detection, between fault detection and possible isolation, and after fault isolation

Reconfigurable cooperative control of networked lagrangian systems under actuator saturation constraints

In this paper, a reconfigurable control strategy is proposed for state synchronization and tracking control of networked (electro-) mechanical Euler-Lagrange (EL) systems that are subject to input saturation constraints that may arise due to actuator faults or failures. The reconfigurable controller consists of three main parts. The first part, known as the nominal controller, is a distributed controller that is employed to guarantee global stability of the multiagent networked EL system provided that certain mild connectivity conditions are satisfied in absence or presence of actuator saturation constraints. The second part, known as the reconfigured controller, is a constrained nonlinear smooth distributed controller that has a different structure and gains from the nominal controller. This controller can preserve the overall control objectives in presence of actuator faults and actuator saturation constraints. The third part is a switching strategy between the nominal and the reconfigured controllers. Global stability as well as asymptotic convergence of the synchronization and the tracking errors to origin for switchings under certain conditions between the nominal and the reconfigured controllers with non-vanishing dwell-times for a fixed network topology are shown to be guaranteed. Simulation results are reported to demonstrate and validate the merits of the proposed controllers