Guaranteed-performance resilient consensus for multi-agent systems subject to actuator attacks

ABSTRACTIn this paper, we develop a novel distributed adaptive control architecture for addressing networked multiagent systems subject to stochastic exogenous disturbances with compromised sensor and actuators. Specifically, for a class of linear leader–follower multiagent systems, we develop a new structure of the neighbourhood synchronisation error for the control design protocol of each follower. The proposed control algorithm addresses time-varying multiplicative sensor attacks on the leader state measurements. In addition, the framework addresses time-varying multiplicative actuator attacks on the followers that do not have a communication link with the leader and additive actuator attacks on all follower agents in the network. The proposed adaptive controller guarantees uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.

In this paper, we develop a novel distributed adaptive control architecture for addressing networked multiagent systems subject to stochastic exogenous disturbances with compromised sensor and actuators. Specifically, for a class of linear leader-follower multiagent systems, we develop a new structure of the neighborhood synchronization error for the control design protocol of each follower. The proposed control algorithm addresses time-varying multiplicative sensor attacks on the leader state measurements. In addition, the framework addresses time-varying multiplicative actuator attacks on the followers that do not have a communication link with the leader and additive actuator attacks on all follower agents in the network. The proposed adaptive controller guarantees uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.

consensus problem of multi agent systems catch great attention in recent years. It is mainly due to its vast applications. Designing an appropriate control protocol that guarantees the desired agreement between the agents is the main purpose of the consensus problem. A linear matrix inequality (LMI)-based approach for the H_∞ consensus of leader-follower nonlinear multi-agent system (MAS) is proposed in this paper. In the proposed framework, fuzzy Lyuponov function (FLF) is chosen. Some slack matrices are introduced to decouple the Lyapunov matrices from the systems' one which provide more degrees of freedom to the consensus problem and leads to decrease the conservativeness. As a result, sufficient conditions for consensus problem are presented in terms of LMIs. Finally, In order to evaluate the validity and effectiveness of the proposed approach, a numerical example for consensus of nonlinear MAS with thirteen followers is solved and simulation results are provided. Obtained results demonstrate the solid validity and great effectiveness of the proposed approach.

In this paper, distributed state and output feedback adaptive consensus control protocols are developed for addressing networked multiagent systems subject to exogenous stochastic disturbances as well as sensor and actuator attacks. Specifically, for a class of linear leader–follower multiagent systems with an undirected communication graph topology, state and output feedback adaptive control design protocols are developed for each follower agent to address malicious attacks on the actuator signals of the follower agents as well as sensor attacks on the state and output neighborhood synchronization error measurements. The proposed adaptive controllers involve an indirect adaptive architecture that estimates and compensates for the malicious attacks while guaranteeing uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.

Distributed consensus is an important class of distributed algorithms and has attracted great interests in recent years in multi-agent systems, but it introduces a new security issue that adversarial agents may manipulate false information to disrupt the correct operation of consensus process of the whole network. This paper institutes the resilient consensus problem of multi-agent networks under limited communication. The communication channels among the nodes are constrained in which the exchanged information is quantized. The objective is to design a quantized-data based control protocol so that the safe agents can withstand the attackers and acquire an agreement as time goes to infinity. Finally, an example and simulation results are given to illustrate the effectiveness of the algorithm.

Cyber attacks threaten the security of cyber-physical systems (CPSs) seriously. Resilient control has been studied to defend cyber attacks. However, existing resilient control schemes have not considered system structure changes caused by actuator attacks. Such structure changes are more destructive and harmful than the actuator attack scenarios investigated in the literature, demanding new resilient control strategies. They will be addressed in this article in cloud computing environments, which are increasingly deployed in large-scale CPSs. More specifically, a resilient control scheme is designed which consists of two controllers: a local resilient controller and cloud-based resilient controller. The local resilient controller withstands actuator attacks that simply tampers the actuator output to a large extent. The cloud-based resilient controller aims to resist the actuator attacks that destroy the system structure. Simulations are conducted on a permanent synchronous motor control system to demonstrate the proposed resilient control scheme.

Although quite a few results on resilient consensus of multi-agent systems with malicious agents and fixed topology have been reported in the literature, we lack any known results on such a problem for multi-agent systems with time-varying topologies. Herein, we study the resilient consensus problem of time-varying networked systems in the presence of misbehaving nodes. A novel concept of joint ( r, s) -robustness is firstly proposed to characterize the robustness of the time-varying topologies. It is further revealed that the resilient consensus of multi-agent systems under F-total malicious network can be reached by the Weighted Mean-Subsequence-Reduced algorithm if and only if the time-varying graph is jointly ( F+1, F+1) -robust. Numerical simulations are finally performed to verify the effectiveness of the analytical results.

This paper considers the event‐triggered adaptive fuzzy bipartite containment control problem for switched nonlinear multi‐agent systems (MASs) with actuator attacks. To handle the completely unknown nonlinear functions in the considered system, fuzzy logic systems (FLSs) are applied to approximate the unknown nonlinear functions. In addition, an adaptive bipartite containment control approach is designed to deal with the actuator attacks, which can reduce the burden of communication. According to the designed adaptive bipartite containment control scheme, it is shown that all the signals are semi‐globally uniformly ultimately bounded (SGUUB), and all the outputs of the followers achieve the bipartite consensus and finally enter the convex set spanned by leaders' in the presence of actuator attacks. Eventually, a simulation example is presented to illustrate the availability of the developed strategy.

In this paper, the prescribed-instant stability control is proposed and utilized in the leader-follower multiagent system with a directed communication topology. The proposed prescribed-instant stability ensures the settling time is exactly equal to the prescribed time instant. Therefore, the specific time instant at which the system containment is established can be manipulated as per our will. This result is of great significance in some complex multiagent system cooperation tasks. The proof of the main result is demonstrated by the Lyapunov method, Specifically, the settling time is clamped from two sides to the selected time instant. Apart from the theoretical proof, a numerical simulation is also presented to validate the proposed method.

This paper investigates the output consensus tracking problem of a class of heterogeneous open multi-agent systems (oMASs) under actuator attacks. The main challenges in solving this problem stem from the presence of actuator attacks and the dimensionality mismatch of the error signals caused by the dynamic entry and exit of followers. To address such challenges, a novel analytical method is developed to characterize the error evolution at switching instants via switching-instant error-coupling inequalities, which describe how error signals evolve in response to changes in the number of followers. Based on this method, a full-order attack-free state observer is designed to estimate the states of each follower without estimating the exact value of the attack. In addition, a reduced-order attack-free observer is developed to reduce the estimation burden and computational complexity, while still ensuring the effective estimation of the states. Building on the observer architectures, both full-order and reduced-order observer-based distributed resilient control protocols are proposed to achieve output consensus tracking while ensuring the tracking error remains uniformly ultimately bounded (UUB) for heterogeneous oMAS under actuator attacks, by employing the output regulation approach. The effectiveness of both types of control protocols is demonstrated through numerical simulation.

This work considers the path-following problem for Unmanned Aerial System (UAS) in which an online remote control station computes and sends control input signals to the vehicle over an adverse communication network. In that network configuration, the cyber attackers and malicious eavesdroppers are prone to erode the UAS's safety properties such as operational security and information privacy. To guarantee these properties, we introduce a secure model predictive control (MPC) framework for achieving both optimal and safe path-following performance. The unique feature of this framework is that it can simultaneously address all the adversaries occurring in both remote station and network transmission links. Then, an encrypted MPC law is designed using an effective encoding scheme and the Paillier cryptography scheme. It is shown that the closed-loop stability can be guaranteed under the proposed MPC law. Simulation studies of UAS path-following are conducted to validate the effectiveness of the proposed framework.

A generalized proportional Caputo fractional model of multi-agent linear dynamic systems via impulsive control protocol

The resilient consensus problem is investigated in this paper for a class of networked Euler-Lagrange systems with event-triggered communication in the presence of Byzantine attacks. One challenge that we face in addressing the considered problem is the inapplicability of existing resilient decision algorithms designed for one-dimensional multi-agent systems. This is because the networked Euler-Lagrange systems fall into the category of multi-dimensional multi-agent systems with coupling among state vector components. To address this problem, we propose a new resilient decision algorithm. This algorithm constructs auxiliary variables related to the coordinative objectives for each normal agent, and transforms the considered resilient consensus problem into the consensus problem of the designed auxiliary variables. Furthermore, to relax the constraints imposed on Byzantine agent behavior patterns within continuous-time scenarios, the event-triggered communication scheme is adopted. Finally, the effectiveness of the proposed algorithm is demonstrated through case studies.

SummaryIn this paper, the event‐triggered leader‐following consensus problem of general linear fractional‐order multiagent systems subject to input delay on directed graph is investigated. A distributed event‐triggered control protocol with input delay is proposed firstly. By applying the properties of the Mittag‐Leffler function, the technique of inequality, and the matrix theory, some consensus criteria for the fractional‐order multiagent systems are obtained. It is shown that the dynamic leader can be tracked by the followers for any bounded delay, and the followers receive and update their control protocol at some discrete time instants. Some simulation results are presented to illustrate the effectiveness of the theoretical analysis.

The flocking of multiple intelligent agents, inspired by the swarm behavior of natural phenomena, has been widely used in the engineering fields such as in unmanned aerial vehicle (UAV) and robots system. However, the performance of the system (such as response time, network throughput, and resource utilization) may be greatly affected while the intelligent agents are engaged in cooperative work. Therefore, it is concerned to accomplish the distributed cooperation while ensuring the optimal performance of the intelligent system. In this paper, we investigated the optimal control problem of distributed multiagent systems (MASs) with finite-time group flocking movement. Specifically, we propose two optimal group flocking algorithms of MASs with single-integrator model and double-integrator model. Then, we study the group consensus of distributed MASs by using modern control theory and finite-time convergence theory, where the proposed optimal control algorithms can drive MASs to achieve the group convergence in finite-time while minimizing the performance index of the intelligence system. Finally, experimental simulation shows that MASs can keep the minimum energy function under the effect of optimal control algorithm, while the intelligent agents can follow the optimal trajectory to achieve group flocking in finite time.