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

Optimal Time-Invariant Distributed Formation Tracking for Second-Order Multi-Agent Systems

This paper addresses the optimal time-invariant formation tracking problem with the aim of providing a distributed solution for multi-agent systems with second-order integrator dynamics. In the literature, most of the results related to multi-agent formation tracking do not consider energy issues while investigating distributed feedback control laws. In order to account for this crucial design aspect, we contribute by formalizing and proposing a solution to an optimization problem that encapsulates trajectory tracking, distance-based formation control, and input energy minimization, through a specific and key choice of potential functions in the optimization cost. To this end, we show how to compute the inverse dynamics in a centralized fashion by means of the Projector-Operator-based Newton's method for Trajectory Optimization (PRONTO) and, more importantly, we exploit such an offline solution as a general reference to devise a novel online distributed control law. Finally, numerical examples involving a cubic formation following a straight path in the 3D space are provided to validate the proposed control strategies.Comment: 28 pages, 2 figures, submitted to the European Journal of Control on June 23rd, 2023 (version 1

A Distributed Observer-Based Cyber-Attack Identification Scheme in Cooperative Networked Systems under Switching Communication Topologies

This paper studies an approach for detecting cyber attacks against networked cooperative systems (NCS) that are assumed to be working in a cyber-physical environment. NCS are prone to anomalies both due to cyber and physical attacks and faults. Cyber-attacks being more hazardous given the cooperative nature of the NCS may lead to disastrous consequences and thus need to be detected as soon as they occur by all systems in the network. Our approach deals with two types of malicious attacks aimed at compromising the stability of the NCS: intrusion attacks/local malfunctions on individual systems and deception/cyber-attacks on the communication between the systems. In order to detect and identify such attacks under switching communication topologies, this paper proposes a new distributed methodology that solves global state estimation of the NCS where the aim is identifying anomalies in the networked system using residuals generated by monitoring agents such that coverage of the entire network is assured. A cascade of predefined-time sliding mode switched observers is introduced for each agent to achieve a fast estimate of the global state whereby the settling time is an a priori defined parameter independently of the initial conditions. Then, using the conventional consensus algorithm, a set of residuals are generated by the agents that is capable of detecting and isolating local intrusion attacks and communication cyber-attacks in the network using only locally exchanged information. In order to prove the effectiveness of the proposed method, the framework is tested for a velocity synchronization seeking network of mobile robots

Distributed consensus in multi-robot systems with visual perception

La idea de equipos de robots actuando con autonomía y de manera cooperativa está cada día más cerca de convertirse en realidad. Los sistemas multi robot pueden ejecutar tareas de gran complejidad con mayor robustez y en menos tiempo que un robot trabajando solo. Por otra parte, la coordinación de un equipo de robots introduce complicaciones que los ingenieros encargados de diseñar estos sistemas deben afrontar. Conseguir que la percepción del entorno sea consistente en todos los robots es uno de los aspectos más importantes requeridos en cualquier tarea cooperativa, lo que implica que las observaciones de cada robot del equipo deben ser transmitidas a todos los otros miembros. Cuando dos o más robots poseen información común del entorno, el equipo debe alcanzar un consenso usando toda la información disponible. Esto se debe hacer considerando las limitaciones de cada robot, teniendo en cuenta que no todos los robots se pueden comunicar unos con otros. Con este objetivo, se aborda la tarea de diseñar algoritmos distribuidos que consigan que un equipo de robots llegue a un consenso acerca de la información percibida por todos los miembros. Específicamente, nos centramos en resolver este problema cuando los robots usan la visión como sensor para percibir el entorno. Las cámaras convencionales son muy útiles a la hora de ejecutar tareas como la navegación y la construcción de mapas, esenciales en el ámbito de la robótica, gracias a la gran cantidad de información que contiene cada imagen. Sin embargo, el uso de estos sensores en un marco distribuido introduce una gran cantidad de complicaciones adicionales que deben ser abordadas si se quiere cumplir el objetivo propuesto. En esta Tesis presentamos un estudio profundo de los algoritmos distribuidos de consenso y cómo estos pueden ser usados por un equipo de robots equipados con cámaras convencionales, resolviendo los aspectos más importantes relacionados con el uso de estos sensores. En la primera parte de la Tesis nos centramos en encontrar correspondencias globales entre las observaciones de todos los robots. De esta manera, los robots son capaces de detectar que observaciones deben ser combinadas para el cálculo del consenso. También lidiamos con el problema de la robustez y la detección distribuida de espurios durante el cálculo del consenso. Para contrarrestar el incremento del tamaño de los mensajes intercambiados por los robots en las etapas anteriores, usamos las propiedades de los polinomios de Chebyshev, reduciendo el número de iteraciones que se requieren para alcanzar el consenso. En la segunda parte de la Tesis, centramos nuestra atención en los problemas de crear un mapa y controlar el movimiento del equipo de robots. Presentamos soluciones para alcanzar un consenso en estos escenarios mediante el uso de técnicas de visión por computador ampliamente conocidas. El uso de algoritmos de estructura y movimiento nos permite obviar restricciones tales como que los robots tengan que observarse unos a otros directamente durante el control o la necesidad de especificar un marco de referencia común. Adicionalmente, nuestros algoritmos tienen un comportamiento robusto cuando la calibración de las cámaras no se conoce. Finalmente, la evaluación de las propuestas se realiza utilizando un data set de un entorno urbano y robots reales con restricciones de movimiento no holónomas. Todos los algoritmos que se presentan en esta Tesis han sido diseñados para ser ejecutados de manera distribuida. En la Tesis demostramos de manera teórica las principales propiedades de los algoritmos que se proponen y evaluamos la calidad de los mismos con datos simulados e imágenes reales. En resumen, las principales contribuciones de esta Tesis son: • Un conjunto de algoritmos distribuidos que permiten a un equipo de robots equipados con cámaras convencionales alcanzar un consenso acerca de la información que perciben. En particular, proponemos tres algoritmos distribuidos con el objetivo de resolver los problemas de encontrar correspondencias globales entre la información de todos los robots, detectar y descartar información espuria, y reducir el número de veces que los robots tienen que comunicarse entre ellos antes de alcanzar el consenso. • La combinación de técnicas de consenso distribuido y estructura y movimiento en tareas de control y percepción. Se ha diseñado un algoritmo para construir un mapa topológico de manera cooperativa usando planos como características del mapa y restricciones de homografía como elementos para relacionar las observaciones de los robots. También se ha propuesto una ley de control distribuida utilizando la geometría epipolar con el objetivo de hacer que el equipo de robots alcance una orientación común sin la necesidad de observarse directamente unos a otros

Fault Detection and Isolation in Controlled Multi-Robot Systems

Multi-Agent Systems (MASs) have attracted much popularity, since the previous decade due to their potential wide range of applications. Indeed, connected MASs are deployed in order to achieve more complex objectives that could otherwise not be achievable by a single agent. In distributed schemes, agents must share their information with their neighbours, which are then used for common control and fault detection purposes, and thus do not require any central monitoring unit. This translates into the necessity to develop efficient distributed algorithms in terms of robustness and safety. Indeed, the problem of safety in connected cooperative MASs has arisen as a consequence of their complexity and the nature of their operations and wireless communication exchanges, which renders them vulnerable to not only physical faults, but also to cyber-attacks. The main focus of this thesis is the study of distributed fault and attack detection and isolation in connected MASs. First, a distributed methodology for global detection of actuator faults in a class of linear MASs with unknown disturbances is proposed using a cascade of fixed-time Sliding Mode Observers (SMOs), where each agent having access to their state, and neighbouring information exchanges, can give an exact estimate of the state of the overall MAS. An LMI-based approach is then applied to design distributed global robust residual signals at each agent capable of detecting faults anywhere in the network. This is then extended to agents with nonlinear nonholonomic dynamics where a new distributed robust Fault Detection and Isolation (FDI) scheme is proposed using predefined-time stability techniques to derive adequate distributed SMOs. This enables to reconstruct the global system state in a predefined-time and generate proper residual signals. The case of MASs with higher order integrator dynamics, where only the first state variable is measurable and the topology is switching is investigated, where a new approach to identify faults and deception attacks is introduced. The proposed protocol makes an agent act as a central node monitoring the whole system activities in a distributed fashion whereby a bank of distributed predefined-time SMOs for global state estimation are designed, which are then used to generate residual signals capable of identifying cyber-attacks despite the switching topology. The problem of attack and FDI in connected heterogeneous MASs with directed graphs, is then studied. First, the problem of distributed fault detection for a team of heterogeneous MASs with linear dynamics is investigated, where a new output observer scheme is proposed which is effective for both directed and undirected topologies. The main advantage of this approach is that the design, being dependant only on the input-output relations, renders the computational cost, information exchange and scalability very effective compared to other FDI approaches that employ the whole state estimation of the agents and their neighbours as a basis for their design. A more general model is then studied, where actuator, sensor and communication faults/attacks are considered in the robust detection and isolation process for nonlinear heterogeneous MASs with measurement noise, dynamic disturbances and communication parameter uncertainties, where the topology is not required to be undirected. This is done using a distributed finite-frequency mixed H_/H1 nonlinear UIO-based approach. Simulation examples are given for each of the proposed algorithms to show their effectiveness and robustness

Bearing-Only Formation Control With Prespecified Convergence Time

This article considers the bearing-only formation control problem, where the control of each agent only relies on relative bearings of their neighbors. A new control law is proposed to achieve target formations in finite time. Different from the existing results, the control law is based on a time-varying scaling gain. Hence, the convergence time can be arbitrarily chosen by users, and the derivative of the control input is continuous. Furthermore, sufficient conditions are given to guarantee almost global convergence and interagent collision avoidance. Then, a leader-follower control structure is proposed to achieve global convergence. By exploring the properties of the bearing Laplacian matrix, the collision avoidance and smooth control input are preserved. A multirobot hardware platform is designed to validate the theoretical results. Both simulation and experimental results demonstrate the effectiveness of our design

Quality-of-service provisioning for dynamic heterogeneous wireless sensor networks

A Wireless Sensor Network (WSN) consists of a large collection of spatially dis- tributed autonomous devices with sensors to monitor physical or environmental conditions, such as air-pollution, temperature and traffic flow. By cooperatively processing and communicating information to central locations, appropriate ac- tions can be performed in response. WSNs perform a large variety of applications, such as the monitoring of elderly persons or conditions in a greenhouse. To correctly and efficiently perform a task, the behaviour of the WSN should be such that sufficient Quality-of-Service (QoS) is provided. QoS is defined by constraints and objectives on network quality metrics, such as a maximum end- to-end packet loss or minimum network lifetime. After defining the application we want the WSN to perform, many steps are involved in designing the WSN such that sufficient QoS is provided. First, a (heterogeneous) set of sensor nodes and protocols need to be selected. Furthermore, a suitable deployment has to be found and the network should be configured for its first use. This configuration involves setting all controllable parameters that influence its behaviour, such as selecting the neighbouring node(s) to communicate to and setting the transmission power of its radio, to ensure that the WSN provides the required QoS. Configuring the network is a complex task as the number of parameters and their possible values are large and trade-offs between multiple quality metrics exist. High transmission power may result in a low packet loss to a neighbouring node, but also in a high power consumption and low lifetime. Heterogeneity in the network causes the impact of parameters to be different between nodes, requiring parameters of nodes to be set individually. Moreover, a static configuration is typically not sufficient to make the most efficient trade-off between the quality metrics at all times in a dynamic environment. Run-time mechanisms are needed to maintain the required level of QoS under changing circumstances, such as changing external interference, mobility of nodes or fluctuating traffic load. This thesis deals with run-time reconfiguration of dynamic heterogeneous wire- less sensor networks to maintain a required QoS, given a deployed network with selected communication protocols and their controllable parameters. The main contribution of this thesis is an efficient QoS provisioning strategy. It consists of three parts: a re-active reconfiguration method, a generic distributed service to estimate network metrics and a pro-active reconfiguration method. In the re-active method, nodes collaboratively respond to discrepancies be- tween the current and required QoS. Nodes use feedback control which, at a given speed, adapts parameters of the node to continuously reduce any error between the locally estimated network QoS and QoS requirements. A dynamic predictive model is used and updated at run-time, to predict how different parameter adap- tations influence the QoS. Setting the speed of adaptation allows us to influence the trade-off between responsiveness and overhead of the approach, and to tune it to the characteristics of the application scenario. Simulations and experiments with an actual deployment show the successful integration in practical scenar- ios. Compared to existing configuration strategies, we are able to extend network lifetime significantly, while maintaining required packet delivery ratios. To solve the non-trivial problem of efficiently estimating network quality met- rics, we introduce a generic distributed service to distributively compute various network metrics. This service takes into account the possible presence of links with asymmetric quality that may vary over time, by repeated forwarding of informa- tion over multiple hops combined with explicit information validity management. The generic service is instantiated from the definition of a recursive local update function that converges to a fixed point representing the desired metric. We show the convergence and stability of various instantiations. Parameters can be set in accordance with the characteristics of the deployment and influence the trade-off between accuracy and overhead. Simulations and experiments show a significant increase in estimation accuracy, and efficiency of a protocol using the estimates, compared to today’s current approaches. This service is integrated in various protocol stacks providing different kinds of network metric estimates. The pro-active reconfiguration method reconfigures in response to predefined run-time detectable events that may cause the network QoS to change signifi- cantly. While the re-active method is generally applicable and independent of the application scenario, the, complementary, pro-active method exploits any a-priori knowledge of the application scenario to adapt more efficiently. A simple example is that as soon as a person with a body sensor node starts walking we know that several aspects, including the network topology, will change. To avoid degradation of network QoS, we pro-actively adapt parameters, in this case, for instance, the frequency of updating the set of neighbouring nodes, as soon as we observe that a person starts to walk. At design time, different modes of operation are selected to be distinguished at run-time. Analysis techniques, such as simulations, are used to determine a suitable configuration for each of these modes. At run time, the approach ensures that nodes can detect the mode in which they should operate. We describe the integration of the pro-active method for two practical monitoring applications. Simulations and experiments show the feasibility of an implementa- tion on resource constrained nodes. The pro-active reconfiguration allows for an efficient QoS provisioning in combination with the re-active approach