Fault-Tolerant Consensus of Multi-Agent System With Distributed Adaptive Protocol

Adaptive Descriptor Sliding-Mode Observer-Based Dynamic Event-Triggered Consensus of Multiagent Systems Against Actuator and Sensor Faults

Actuator and sensor faults are among the most common factors affecting the stability of multiagent systems (MASs). This article proposes a dynamic event-triggered fault-tolerant control (FTC) algorithm based on descriptor sliding-mode observers to address actuator and sensor faults in MASs. First, the MAS dynamics are reformulated into a descriptor form, enabling an observer to simultaneously achieve state estimation and fault diagnosis. Using the estimation results, an adaptive FTC algorithm is developed to maintain the stability of MASs in the presence of concurrent faults, with control gains updated based on the observer consensus error. A dynamic event-triggered mechanism is incorporated to manage data transmission and update neighboring agents' information for the controller, thereby reducing communication overhead. Finally, a numerical simulation involving multiple quadrotors is conducted to validate the effectiveness of the proposed method.

Fault-Tolerant Consensus of Multiagent Systems With Prescribed Performance

This article studies the fault-tolerant consensus problem with the guaranteed transient performance of multiagent systems (MASs) subject to unknown time-varying actuator faults and disturbances. The general actuator faults, including both multiplicative and additive time-varying faults, are considered in such a problem for the first time. Both single-integrator modeled agents and double-integrator modeled agents are investigated. The transient performance is ensured in the sense that position errors between each pair of neighboring agents are guaranteed within certain user-defined time-varying performance bounds. Adaptive laws are designed to estimate information about faults and disturbances. For MASs with additive faults, the proposed controllers ensure errors asymptotically converge to zero with guaranteed transient performance. For MASs with both multiplicative faults and additive faults, the proposed controllers ensure errors converge to a residual set without asymptotic convergence but still with guaranteed transient performance. Two simulation examples are provided to evaluate the proposed schemes.

Dynamic event-triggered consensus control for nonlinear multi-agent systems under DoS attacks

In this paper, we investigated leader-following consensus control for nonlinear multi-agent systems (MASs) experiencing denial-of-service (DoS) attacks. We proposed a distributed control strategy incorporating an adaptive scheme and a state feedback control gain to eliminate the effects of system nonlinear dynamics and uncertainties. In addition, we introduced a dynamic event-triggered control (DETC) to minimize the utilization of communication resources. Finally, we provided simulation results to show the validity of the proposed approach.

Sliding-mode fault-tolerant control of the six-rotor UAV with dead-zone-input under event-triggered mechanism

This paper investigates the problem of event-triggered mechanism(ETM)-based sliding-mode fault-tolerant control (FTC) for a six-rotor Unmanned Aerial Vehicle (UAV) with dead zone input (DZI) cases, considering potential actuator and sensor faults. Initially, a dynamic ETM is designed, followed by the development of a non-fragile observer utilizing this designed ETM. An integral sliding surface (SS) is then designed in the observation space, and the system is augmented and treated as a variable time delay system. Subsequently, sufficient conditions to ensure the stability of the augmented system with an H∞ performance index γ are obtained using the Lyapunov-Krasovskii function. Next, a sliding mode control (SMC) law is formulated to guide the sliding variables to the SS in finite time. Furthermore, sufficient conditions for ensuring system stability with an H∞ performance index γ are decoupled, and the calculation methods for the non-fragile observer gain matrix and the sliding mode gain matrix are obtained. Finally, to validate the effectiveness of the proposed method in this paper, simulation experiments are conducted.

Distributed Adaptive Fault-Tolerant Control for Multiagent Systems via Virtual-Actuator-Based Reconfiguration

This article aims to develop a virtual-actuator-based control scheme for the consensus tracking problem of multiagent systems (MASs) against actuator faults and mismatched disturbances. The proposed scheme has a double-layer structure. In the cyber layer, the nominal controller is designed with neighboring information for the fault-free case. While in the physical layer, the fault compensator, working as the virtual actuator, is applied to reconfigure faulty plants adaptively. This design enjoys the advantages that the nominal controller needs no adjustment and all its properties can be preserved after failure. Moreover, the proposed control scheme is distinguished by the following features: 1) the commonly imposed rank condition on outage faults is removed; 2) the norm bound of the leader's input is allowed to be unknown even though the topologies are switching and directed; and 3) there is no need to use the estimates of faults in the virtual actuator design, which means the negative impacts caused by the inaccurate fault estimation can be avoided. Finally, a numerical example is given to validate the effectiveness of the theoretical results.

Distributed Multiagent-Based Event-Driven Fault-Tolerant Control of Islanded Microgrids

This article proposes an observer-based event-driven fault-tolerant (OBEDFT) secondary control strategy for AC microgrids (MGs) to achieve load voltage regulation. First, the input-output feedback linearization method transforms the voltage regulation issue into an output feedback tracking problem for linear multiagent systems (MASs) with nonlinear dynamics. This transformation provides the necessary preprocessing for load voltage regulation. Then, an OBEDFT secondary control protocol that considers full-state immeasurability is proposed. The actuators of distributed generators (DGs) may experience partial loss of effectiveness (PLOE) and bias faults, and these fault parameters may be heterogeneous and time-varying. The protocol introduces adaptive techniques to avoid information related to fault parameters while using event-driven mechanisms to achieve discrete measurements of neighboring DG. Additionally, the protocol uses boundary layers to construct smooth controllers that prevent the chattering effect caused by nonsmooth controllers. Finally, simulation results confirm the effectiveness of this load voltage regulation strategy.

Adaptive fixed-time consensus for stochastic multi-agent systems with uncertain actuator faults

In this paper, we study the adaptive fixed-time consensus control for stochastic multi-agent systems (SMASs) with uncertain actuator faults. Firstly, a fully distributed adaptive consensus protocol and an adaptive fault-tolerant consensus protocol are proposed, respectively, to ensure that the fixed-time consensus of SMASs with actuator faults can be reached. Secondly, an adaptive fault-tolerant containment consensus protocol is further proposed for the SMASs by leveraging the signum function, and this protocol can effectively solve the containment consensus in the unbalanced communication network. Finally, some simulation examples are given to verify the effectiveness of our consensus protocols.

Double Model Following Adaptive Control for a Complex Dynamical Network

This paper formulates and solves a new problem of the double model following adaptive control (MFAC) of nodes and links in a complex dynamical network (CDN). This is different from most existing studies on CDN and MFAC. Inspired by the concept of composite systems, the CDN with dynamic links is regarded as an interconnected system composed of an interconnected node group (NG) and link group (LG). Guided by the above-mentioned new idea of viewing a CDN from the perspective of composite systems, by means of Lyapunov theory and proposed related mathematical preliminaries, a new adaptive control scheme is proposed for NG. In addition, to remove the restriction that the states of links in a CDN are unavailable due to physical constraints, technical restraints, and expensive measurement costs, we synthesize the coupling term in LG with the proposed adaptive control scheme for NG, such that the problem of double MFAC of nodes and links in CDN is solved. Finally, a simulation example is presented to verify the theoretical results.

Distributed Bipartite Adaptive Event-Triggered Fault-Tolerant Consensus Tracking for Linear Multiagent Systems Under Actuator Faults

This article considers the distributed bipartite adaptive event-triggered fault-tolerant consensus tracking issue for linear multiagent systems in the presence of actuator faults based on the output feedback control protocol. Both time-varying additive and multiplicative actuator faults are taken into account in the meantime. And the upper/lower bounds of actuator faults are not required to be known. First, the state observer is designed to settle the occurrence of unmeasurable system states. Two kinds of event-triggered mechanisms are then developed to schedule the interagent communication and controller updates. Next, with the developed event-triggered mechanisms, a novel observer-based bipartite adaptive control strategy is proposed such that the fault-tolerant control problem can be addressed. Compared with some related works on this topic, our control scheme can achieve the intermittent communication and intermittent controller updates, and the more general actuator faults and network topology are considered. It is proved that the exclusion of Zeno behavior can be realized. Finally, three illustrative examples are given to demonstrate the feasibility of the main theoretical findings.

Fully Distributed Adaptive Event-Triggered Control of Networked Systems With Actuator Bias Faults

In this article, the problem of distributed synchronization of networked systems with actuator bias faults is investigated. To effectively use the limited network bandwidth and avoid the requirement of global information, a novel adaptive event-triggered state feedback controller and a dynamic triggering law are designed jointly by employing a projection operator approach. The proposed synchronization scheme is different from existing ones that have focused on designing controllers and triggering laws independently. Besides, our scheme is extended to design an observer-based distributed adaptive event-triggered controller and corresponding dynamic triggering law when the system states are unmeasurable. Theoretical analysis shows that under the two different distributed event-triggered synchronization schemes, the following three results can be obtained: 1) fully distributed synchronization can be achieved without knowing global information associated with the underlying communication topology and node's scale; 2) continuous communication among adjacent nodes can be avoided for both designed controllers and dynamic triggering laws; and 3) exclusion of Zeno phenomenon is shown by contradiction. Finally, the effectiveness of the proposed algorithms is verified through three numerical examples.

Adaptive Fault-Tolerant Formation Control of Heterogeneous Multi-Agent Systems under Directed Communication Topology

This paper investigates the adaptive fault-tolerant formation control scheme for heterogeneous multi-agent systems consisting of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) with actuator faults, parameter uncertainties and external disturbances under directed communication topology. Firstly, the dynamic models of UAVs and USVs are introduced, and a unified heterogeneous multi-agent system model with actuator faults is established. Then, a distributed fault-tolerant formation controller is proposed for the unified model of UAVs and USVs in the XY plane by using adaptive updating laws and radial basis function neural network. After that, a decentralized formation-tracking controller is designed for the altitude control system of UAVs. Based on the Lyapunov stability theory, it can be proved that the formation errors and tracking errors are uniformly ultimately bounded which means that the expected time-varying formation is achieved. Finally, a simulation study is given to demonstrate the effectiveness of the proposed scheme.

Fully Distributed Adaptive Finite-Time Consensus for Uncertain Nonlinear Multiagent Systems

In this article, the adaptive finite-time consensus problem is discussed for uncertain nonlinear multiagent systems. In contrast with the correlative literature, the systems permit multiple uncertainties (not only in control coefficients but also in inherent nonlinearities), and typically the consensus protocol is pursued in a fully distributed fashion (independent from any global information of network topology). This essentially challenges the realization of the finite-time consensus. To overcome the challenge, a new continuous fully distributed protocol is proposed by combining adaptive techniques such that the finite-time consensus of the systems under investigation is achieved. Remarkably, a dynamic high gain, rather than multiple ones in the related literature, is adequate to resist two kinds of uncertainties and to guarantee the fully distributed fashion of the consensus protocol. Moreover, the adaptive finite-time consensus protocol is specified on the scenario of leader-following multiagent systems. Simulation results of three interaction topologies are acquired to illustrate the validity and the wider applicability of the proposed protocol.

Fully Distributed Adaptive Fault-Tolerant Sliding-Mode Control for Nonlinear Leader-Following Multiagent Systems With ANASs and IQCs

In this article, by combining the skills of the pseudo-PID sliding-mode control (SMC) method with adaptive control techniques, two novel fully distributed adaptive fault-tolerant control strategies are proposed to handle the leader-following consensus problem of nonlinear multiagent systems with integral quadratic constraints (IQCs) and actuator faults, with and without asymmetric nonlinear actuator saturations (ANASs). For the no-saturation case, the designed controller has a simple structure and low computation but requires the crude information of the system model. To overcome this weakness, for the saturation case, the controller is redesigned by introducing a novel anti-windup compensator and fuzzy-logic systems (FLSs), where the problem of reducing computational complexity is also considered. The controllers only need local neighbor information instead of global topology information and ensure the practical consensus of the leader-following systems in finite time. Finally, simulation results demonstrate the effectiveness of the proposed approaches.

RNN-K: A Reinforced Newton Method for Consensus-Based Distributed Optimization and Control Over Multiagent Systems

With the rise of the processing power of networked agents in the last decade, second-order methods for machine learning have received increasing attention. To solve the distributed optimization problems over multiagent systems, Newton's method has the benefits of fast convergence and high estimation accuracy. In this article, we propose a reinforced network Newton method with K -order control flexibility (RNN-K) in a distributed manner by integrating the consensus strategy and the latest knowledge across the network into local descent direction. The key component of our method is to make the best of intermediate results from the local neighborhood to learn global knowledge, not just for the consensus effect like most existing works, including the gradient descent and Newton methods as well as their refinements. Such a reinforcement enables revitalizing the traditional iterative consensus strategy to accelerate the descent of the Newton direction. The biggest difficulty to design the approximated Newton descent in distributed settings is addressed by using a special Taylor expansion that follows the matrix splitting technique. Based on the truncation on the Taylor series, our method also presents a tradeoff effect between estimation accuracy and computation/communication cost, which provides the control flexibility as a practical consideration. We derive theoretically the sufficient conditions for the convergence of the proposed RNN-K method of at least a linear rate. The simulation results illustrate the performance effectiveness by being applied to three types of distributed optimization problems that arise frequently in machine-learning scenarios.

Adaptive Coordinated Formation Control of Heterogeneous Vertical Takeoff and Landing UAVs Subject to Parametric Uncertainties

This article focuses on the solution to the coordinated formation problem of heterogeneous vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) in the presence of parametric uncertainties. In particular, their inertial parameters are distinct and unavailable. For the sake of the accomplishment of the coordinated formation objective of multiple underactuated VTOL UAVs through local information exchange, an adaptive distributed control algorithm is developed under a cascaded structure. Specifically, by introducing an immersion and invariance (I&I) adaption strategy for the exponential mass estimation, a distributed command force is first synthesized in the position loop. Next, an applied torque with adaption is synthesized for the attitude tracking to a command attitude. This command attitude, as well as the applied thrust, is extracted from the synthesized command force without singularity. It is shown in terms of the Lyapunov theory that driven by the proposed adaptive distributed control algorithm, the concerned coordinated formation control of multiple VTOL UAVs is achieved asymptotically. Finally, an illustrative example is simulated to validate the effectiveness of the proposed control algorithm.

Distributed Fault-Tolerant Containment Control for Linear Heterogeneous Multiagent Systems: A Hierarchical Design Approach

In this article, the problem of distributed hierarchical fault-tolerant containment control for heterogeneous linear multiagent systems (MASs) is investigated. In most of the existing distributed methods for MASs with system failures, each agent broadcasts its state, or output, or the estimation of state to neighbors. Once an agent is subjected system failures, faults affect the dynamics of other agents over the network, that is, the influence of faults on the agent will propagate with the network. In order to overcome this drawback, a fault-tolerant hierarchical containment control protocol is developed, which includes two layers: 1) the upper layer and 2) the lower layer. The upper layer consists of a virtual system and a cooperative controller to achieve a virtual containment objective. The lower layer consists of an actual system and a fault-tolerant controller to track the upper layer virtual system. Compared with the existing results, the phenomenon of fault propagation can be avoided by introducing the hierarchical design approach, that is, the fault of agent i only affects the dynamics of itself, and does not affect the dynamics of other agents through the network. It is shown that each follower converges asymptotically to a convex hull spanned by leaders with external input. Finally, the developed method is demonstrated by simulation results.

Output Consensus for Heterogeneous Linear Multiagent Systems With a Predictive Event-Triggered Mechanism

In this paper, an output consensus problem for a heterogeneous linear multiagent system with a predictive event-triggered mechanism on directed graphs is investigated. An event-triggered consensus protocol is proposed by introducing an internal reference model for each agent to handle the heterogeneity existing in the system. With the proposed mechanism, each agent predicts its internal reference model's input by employing the estimate of the internal reference model's state differences between itself and its neighbor agents. As it considers the internal reference model's inputs of agents, the system requires far fewer event-triggered times to achieve consensus, leading to a significant reduction in communication cost among agents. A necessary and sufficient condition of the output consensus for the heterogeneous linear multiagent system is put forth. Furthermore, Zeno behavior can be ruled out for each agent. Some numerical examples are given to demonstrate the effectiveness of the proposed control mechanism.

Necessary and Sufficient Conditions for Group Consensus of Fractional Multiagent Systems Under Fixed and Switching Topologies via Pinning Control

The group consensus problem for fractional-order multiagent systems is investigated in this paper. With the help of double-tree-form transformations, the group consensus problem of fractional-order multiagent systems is proved to be equivalent to the asymptotical stability problem of reduced-order error systems. A class of distributed control protocols and some simple LMI sufficient conditions as well as necessary and sufficient conditions are proposed in this paper to solve the group consensus problem for fractional multiagent systems. Moreover, pinning control strategy has been taken into consideration. It is shown that the system converges more rapidly when the designed pinning protocols are adopted. In addition, the case of fractional system with switching topologies is also discussed and some corresponding sufficient conditions are obtained. Finally, some simulation results are presented to illustrate the theoretical results.

Cooperative Fault-Tolerant Output Regulation for Multiagent Systems by Distributed Learning Control Approach

In this article, a new distributed learning control approach is proposed to address the cooperative fault-tolerant output regulation problem for linear multiagent systems with actuator faults. First, a distributed estimation algorithm with an online learning mechanism is presented to identify the system matrix of the exosystem and to estimate the state of the exosystem. In particular, an auxiliary variable is introduced in the distributed estimation algorithm to construct a data matrix, which is used to learn the system matrix of the exosystem for each subsystem. In addition, by resetting the state of the estimator and by using the identified matrix to update the estimator, all subsystems can reconstruct the state of the exosystem at an initial period of time, which is used for the neighbor subsystem to learn the system matrix of the exosystem. Based on the designed estimator, a novel distributed fault-tolerant controller is developed. Compared with the existing cooperative output regulation results, the system matrix of the exosystem considered in this article is unknown for all subsystems. Finally, a simulation example is provided to show the effectiveness of the obtained new design techniques.

Discrete Sliding Mode Control Design for Bilateral Teleoperation System via Adaptive Extended State Observer

The goal of this paper is to improve the synchronization control performance of nonlinear teleoperation systems with system uncertainties in the presence of time delays. In view of the nonlinear discrete states of the teleoperation system in packet-switched communication networks, a new discrete sliding mode control (DSMC) strategy is performed via a new reaching law in task space. The new reaching law is designed to reduce the chattering and improve control performance. Moreover, an adaptive extended state observer (AESO) is used to estimate the total system disturbances. The additional gain of AESO is adjusted in time to decrease the estimation errors of both system states and disturbances automatically and improve the estimation performances of the AESO. Finally, the validity of the designed control strategy is demonstrated by both simulation and experiments. Furthermore, the experimental comparison results indicate that the improvement is achievable with the proposed AESO and DSMC.

Adaptive fault-tolerant time-varying formation tracking for multi-agent systems under actuator failure and input saturation

This paper studies the time-varying formation tracking problem for general linear multi-agent systems with multiple leaders in the presence of both actuator failure and input saturation. The followers are required to uniquely determine and track the convex combination of the states of leaders, while maintaining a predefined time-varying formation. A hyperbolic tangent function is firstly introduced to modify the actuator model with input saturation constraint. Then, an augmented plant for dynamics of each follower is constructed to derive the control protocol by exploiting the dynamic surface control technique. The proposed control protocol deals with faults of bias and unknown bounded loss of effectiveness by means of adaptive fault-tolerant strategies, while a formation feasible condition should be satisfied. With the control signal generated by the augmented plant, the time-varying formation error is proved to be semi-globally uniformly bounded under the faults and input saturation, based on standard Lyapunov theory. Finally, a numerical simulation is implemented to demonstrate the effectiveness of the proposed algorithm.

Distributed Control of Nonlinear Multiagent Systems With Unknown and Nonidentical Control Directions via Event-Triggered Communication

In this paper, the leader-following output consensus problem for a class of uncertain nonlinear multiagent systems with unknown control directions is investigated. Each agent system has nonidentical dynamics and is subject to external disturbances and uncertain parameters. The agents are connected through a directed and jointly connected switching network. A novel two-layer distributed hierarchical control scheme is proposed. In the upper layer, to save the communication resources and to handle the switching networks, an event-triggered communication scheme is proposed, and a Zeno-free event-triggered mechanism is designed for each agent to generate the asynchronous triggering time instants. Furthermore, to avoid the continuous monitoring of the system states, a Zeno-free self-triggering algorithm is proposed. In the lower layer, to handle the unknown control directions problem and to achieve the output tracking of the local references generated in the upper layer, the Nussbaum-type function-based technique is combined with internal model principle. With the proposed two-layer distributed hierarchical controller, the leader-following output consensus is achieved. The obtained result is further extended to the formation control problem. Finally, three numerical examples are provided to demonstrate the effectiveness of the proposed theoretical results.

Impulsive Consensus of Multiagent Systems With Limited Bandwidth Based on Encoding-Decoding

Energy constrains are always significant to be considered in control of multiagent systems. Besides, nonlinear phenomena are often involved into such systems. In this paper, we discuss the impulsive consensus problem of nonlinear multiagent systems via impulsive protocol with limited bandwidth communication based on encoding-decoding. The scheme based on encoding-decoding with impulsive protocol is introduced to multiagent systems in general directed networks topology of which the graph is strongly connected. The impulsive protocols and limited bandwidth communication enhance the performance on energy saving and the involvement of nonlinear dynamics could suit more real-world cases. The design of encoders and decoders is presented, which is the key to achieve the goal that the information exchanged is subject to limited bandwidth communication. The conditions to guarantee the impulsive consensus and the conditions to avoid quantizer saturation are obtained. Moreover, the convergence rate of such multiagent systems are also characterized by the analysis of the exponential consensus. The numerical simulations are presented to support the theoretical results.

Adaptive Fault-Tolerant Consensus Protocols for Multiagent Systems With Directed Graphs

This paper investigates the problem of adaptive fault-tolerant tracking control for the multiagent systems (MASs) under the time-varying actuator faults and bounded unknown control input of the leader. On the basis of the local state information of neighboring agents, an adaptive fault-tolerant control protocol, which consists of the adaptive estimation of faults, is constructed to compensate for the loss of actuator effectiveness in the leader-follower consensus of MASs. Moreover, the modification term in the adaptive estimation can avoid high-frequency oscillations. It is shown that the tracking errors converge to a neighborhood around the origin in the presence of actuator faults, and the performance of the tracking problem is improved. Furthermore, the protocol is distributed in the sense that the coupling gains are independent. Finally, two examples are given to show the effectiveness of the proposed control protocol.

Adaptive Compensation for Nonlinear Time-Varying Multiagent Systems With Actuator Failures and Unknown Control Directions

This paper investigates a problem of designing an adaptive asymptotic cooperative control scheme for nonlinear time-varying multiagent systems, which can simultaneously tolerate unknown actuator failures and unknown control directions. To address such the problem, we propose a conditional inequality, which allows multiple piecewise Nussbaum functions to acquire the control robustness. Benefiting from this robustness, a part of failure uncertainties and system errors are compensated for, while the remaining parts are handled by adaptive control technique. Moreover, structural properties of the proposed adaptive laws are utilized so that Barbalat's lemma is applicable to make all the followers asymptotically converge to the leader based on the neighborhood information.

Input Time Delay Margin in Event-Triggered Consensus of Multiagent Systems

In this paper, the event-triggered consensus problem of multiagent systems with input time delay is investigated. First, the normal event-triggered control scheme containing the input time delay is introduced to reduce the number of communication. Then the following results are achieved: 1) the procedure of setting parameters is carefully formulated for the event-triggered control scheme; 2) the precise input time delay margin is calculated for the event-triggered consensus of the multiagent systems; 3) a more general condition of constructing event-triggered functions is derived to exclude the Zeno behavior; 4) the self-triggered control scheme is further applied to avoid the continuous measurement; and 5) the observer-based control scheme is also utilized to tackle the problem of unmeasurable state. Finally, the correctness and the effectiveness of these results are demonstrated by numerical simulations.

Distributed Adaptive Event-Triggered Fault-Tolerant Consensus of Multiagent Systems With General Linear Dynamics

In this paper, the distributed adaptive event-triggered fault-tolerant consensus of general linear multiagent systems (MASs) is considered. First, in order to deal with multiplicative fault, a distributed event-triggered consensus protocol is designed. Using distributed adaptive online updating strategies, the computation of the minimum eigenvalue of Laplacian matrix is avoided. Second, some adaptive parameters are introduced in trigger function to improve the self-regulation ability of event-triggered mechanism. The new trigger threshold is both state-dependent and time-dependent, which is independent of the number of agents. Then sufficient conditions are derived to guarantee the leaderless and leader-following consensus. On the basis of this, the results are extended to the case of actuator saturation. It is proved the Zeno-behavior of considered event-triggered mechanism is avoided. At last, the effectiveness of the proposed methods are demonstrated by three simulation examples.

Cooperative Fault Tolerant Tracking Control for Multiagent Systems: An Intermediate Estimator-Based Approach

This paper studies the observer based fault tolerant tracking control problem for linear multiagent systems with multiple faults and mismatched disturbances. A novel distributed intermediate estimator based fault tolerant tracking protocol is presented. The leader's input is nonzero and unavailable to the followers. By applying a projection technique, the mismatched disturbances are separated into matched and unmatched components. For each node, a tracking error system is established, for which an intermediate estimator driven by the relative output measurements is constructed to estimate the sensor faults and a combined signal of the leader's input, process faults, and matched disturbance component. Based on the estimation, a fault tolerant tracking protocol is designed to eliminate the effects of the combined signal. Besides, the effect of unmatched disturbance component can be attenuated by directly adjusting some specified parameters. Finally, a simulation example of aircraft demonstrates the effectiveness of the designed tracking protocol.

Fully Distributed Adaptive Consensus Control of a Class of High-Order Nonlinear Systems With a Directed Topology and Unknown Control Directions

In this paper, we investigate the adaptive consensus control for a class of high-order nonlinear systems with different unknown control directions where communications among the agents are represented by a directed graph. Based on backstepping technique, a fully distributed adaptive control approach is proposed without using global information of the topology. Meanwhile, a novel Nussbaum-type function is proposed to address the consensus control with unknown control directions. It is proved that boundedness of all closed-loop signals and asymptotically consensus tracking for all the agents' outputs are ensured. In simulation studies, a numerical example is illustrated to show the effectiveness of the control scheme.

Distributed fault-tolerant time-varying formation control for high-order linear multi-agent systems with actuator failures

This paper investigates the fault-tolerant time-varying formation control problems for high-order linear multi-agent systems in the presence of actuator failures. Firstly, a fully distributed formation control protocol is presented to compensate for the influences of both bias fault and loss of effectiveness fault. Using the adaptive online updating strategies, no global knowledge about the communication topology is required and the bounds of actuator failures can be unknown. Then an algorithm is proposed to determine the control parameters of the fault-tolerant formation protocol, where the time-varying formation feasible conditions and an approach to expand the feasible formation set are given. Furthermore, the stability of the proposed algorithm is proven based on the Lyapunov-like theory. Finally, two simulation examples are given to demonstrate the effectiveness of the theoretical results.

Robust adaptive fault-tolerant control for leader-follower flocking of uncertain multi-agent systems with actuator failure

In this work, we study the flocking problem of multi-agent systems with uncertain dynamics subject to actuator failure and external disturbances. By considering some standard assumptions, we propose a robust adaptive fault tolerant protocol for compensating of the actuator bias fault, the partial loss of actuator effectiveness fault, the model uncertainties, and external disturbances. Under the designed protocol, velocity convergence of agents to that of virtual leader is guaranteed while the connectivity preservation of network and collision avoidance among agents are ensured as well.

Active Complementary Control for Affine Nonlinear Control Systems With Actuator Faults

This paper is concerned with the problem of active complementary control design for affine nonlinear control systems with actuator faults. The outage and loss of effectiveness fault cases are considered. In order to achieve the performance enhancement of the faulty control system, the complementary control scheme is designed in two steps. Firstly, a novel fault estimation scheme is developed. Then, by using the fault estimations to reconstruct the faulty system dynamics and introducing a cost function as the optimization objective, a nearly optimal complementary control is obtained online based on the adaptive dynamic programming (ADP) method. Unlike most of the previous ADP methods with the addition of a probing signal, new adaptive weight update laws are derived to guarantee the convergence of neural network weights and the stability of the closed-loop system, which strongly supports the online implementation of the ADP method. Finally, two simulation examples are given to illustrate the performance and effectiveness of the proposed method.

Controllability and Synchronization Analysis of Identical-Hierarchy Mixed-Valued Logical Control Networks

This paper investigates the controllability and synchronization problems for identical-hierarchy mixed-valued logical control networks. The logical network considered is hierarchical, and Boolean network is a special case of logical network. Here, identical-hierarchy means that there are identical number of nodes in each layer of logical network and corresponding nodes have the same dimension for any two layers of logical networks. Meanwhile, in each layer of logical networks, the dimensions of nodes are distinct, and it is called a mixed-valued logical network. First, the controllability problem is investigated and two notions of controllability are presented, i.e., group-controllability and simultaneously-controllability. By resorting to Perron-Frobenius theorem, some necessary and sufficient criteria are obtained to guarantee group-controllability and simultaneously-controllability, respectively. Second, based on the algebraic representation of the studied model, synchronization problems are analytically discussed for two types of controls, i.e., free control sequences and state-output feedback control. Finally, two numerical examples are presented to show the validness of our main results.

Consensus Tracking of Heterogeneous Discrete-Time Networked Multiagent Systems Based on the Networked Predictive Control Scheme

This paper studies the problem of consensus tracking for heterogeneous discrete-time networked multiagent systems (NMASs) with network-induced communication delay. By introducing the networked predictive control scheme, novel consensus tracking protocols are designed to ensure that states of the NMASs follow the external reference signal. One of the agents is defined as the leader agent, all the other agents are defined as the followers, and the external reference signal is always known by the leader agent, both cases where the external reference signal is available and unavailable to the follower agents are discussed in this paper. The necessary and sufficient conditions for the novel consensus tracking protocols are proposed based on algebraic and graph theory. Numerical examples are given to validate the theoretical results.

Necessary and Sufficient Conditions for Consensus of Second-Order Multiagent Systems Under Directed Topologies Without Global Gain Dependency

The consensus problem for second-order multiagent systems with absolute velocity damping under directed topologies is investigated. In contrast to the existing results, which rely on a sufficiently large common absolute velocity damping gain above a lower bound dependent on global information, this paper focuses on novel algorithms to overcome this limitation. A novel consensus algorithm, where different agents use different absolute velocity damping gains, is first proposed. In the absence of delays, based on a system transformation method, the consensus problem for second-order multiagent systems is converted into that for first-order multiagent systems with the agent number doubled. Necessary and sufficient conditions are then derived under directed topologies by relating the topologies associated with the doubled number of agents and the original team of agents. In the presence of multiple constant delays, based on a further system transformation method, the consensus problem for second-order multiagent systems is converted into the stability problem for corresponding systems. Necessary and sufficient conditions are presented to guarantee consensus under a directed fixed topology. For systems with a uniform constant delay, more concrete necessary and sufficient conditions on how large the delay can be to guarantee consensus is given. Numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results.

Finite-Horizon ${\mathcal H}_{\infty }$ Consensus Control of Time-Varying Multiagent Systems With Stochastic Communication Protocol

This paper is concerned with the distributed ℋ∞ consensus control problem for a discrete time-varying multiagent system with the stochastic communication protocol (SCP). A directed graph is used to characterize the communication topology of the multiagent network. The data transmission between each agent and the neighboring ones is implemented via a constrained communication channel where only one neighboring agent is allowed to transmit data at each time instant. The SCP is applied to schedule the signal transmission of the multiagent system. A sequence of random variables is utilized to capture the scheduling behavior of the SCP. By using the mapping technology combined with the Hadamard product, the closed-loop multiagent system is modeled as a time-varying system with a stochastic parameter matrix. The purpose of the addressed problem is to design a cooperative controller for each agent such that, for all probabilistic scheduling behaviors, the ℋ∞ consensus performance is achieved over a given finite horizon for the closed-loop multiagent system. A necessary and sufficient condition is derived to ensure the ℋ∞ consensus performance based on the completing squares approach and the stochastic analysis technique. Then, the controller parameters are obtained by solving two coupled backward recursive Riccati difference equations. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme.

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

Consensus of Multiagent Systems Subject to Partially Accessible and Overlapping Markovian Network Topologies

This paper addresses the consensus problem for a continuous-time multiagent system (MAS) with Markovian network topologies and external disturbance. Different from some existing results, global jumping modes of the Markovian network topologies are not required to be completely available for consensus protocol design. A network topology mode regulator (NTMR) is first developed to decompose unavailable global modes into several overlapping groups, where overlapping groups refer to the scenario that there exist commonly shared local modes between any two distinct groups. The NTMR schedules which group modes each agent may access at every time step. Then a new group mode-dependent distributed consensus protocol on the basis of relative measurement outputs of neighboring agents is delicately constructed. In this sense, the proposed consensus protocol relies only on group and partial modes and eliminates the need for complete knowledge of global modes. Sufficient conditions on the existence of desired distributed consensus protocols are derived to ensure consensus of the MAS with a prescribed $H_{\infty }$ performance level. Two examples are provided to show the effectiveness of the proposed consensus protocol.

Distributed Fault-Tolerant Control of Networked Uncertain Euler-Lagrange Systems Under Actuator Faults

This paper investigates the distributed fault-tolerant control problem of networked Euler-Lagrange systems with actuator and communication link faults. An adaptive fault-tolerant cooperative control scheme is proposed to achieve the coordinated tracking control of networked uncertain Lagrange systems on a general directed communication topology, which contains a spanning tree with the root node being the active target system. The proposed algorithm is capable of compensating for the actuator bias fault, the partial loss of effectiveness actuation fault, the communication link fault, the model uncertainty, and the external disturbance simultaneously. The control scheme does not use any fault detection and isolation mechanism to detect, separate, and identify the actuator faults online, which largely reduces the online computation and expedites the responsiveness of the controller. To validate the effectiveness of the proposed method, a test-bed of multiple robot-arm cooperative control system is developed for real-time verification. Experiments on the networked robot-arms are conduced and the results confirm the benefits and the effectiveness of the proposed distributed fault-tolerant control algorithms.

Distributed Secure Coordinated Control for Multiagent Systems Under Strategic Attacks

This paper studies a distributed secure consensus tracking control problem for multiagent systems subject to strategic cyber attacks modeled by a random Markov process. A hybrid stochastic secure control framework is established for designing a distributed secure control law such that mean-square exponential consensus tracking is achieved. A connectivity restoration mechanism is considered and the properties on attack frequency and attack length rate are investigated, respectively. Based on the solutions of an algebraic Riccati equation and an algebraic Riccati inequality, a procedure to select the control gains is provided and stability analysis is studied by using Lyapunov's method.. The effect of strategic attacks on discrete-time systems is also investigated. Finally, numerical examples are provided to illustrate the effectiveness of theoretical analysis.