H∞ Containment Control of Multiagent Systems Under Event-Triggered Communication Scheduling: The Finite-Horizon Case

Finite-time tolerant containment control for IT2 T-S fuzzy network multi-agent systems with actuator faults, packet dropouts and DoS attacks

This article studies finite-time tolerant containment control issue for uncertain nonlinear networked multi-agent systems (MASs) with actuator faults, denial-of-service (DoS) attacks and packet dropouts, under the framework of interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy method. Firstly, based on establishing the actuator fault models and introducing Bernoulli random distribution to represent the packet dropouts phenomenon, the IT2 T-S fuzzy network MASs under actuator faults and packet dropouts are constructed as switchable systems according to the attack situations on the communication channels. Secondly, the slack matrix with more information of lower and upper membership functions is introduced in the stability analysis to reduce conservatism. And on basis of Lyapunov stability theory and average dwell-time method, finite-time tolerant containment control protocol is proposed, which makes the follower' states converge to the convex hull controlled by the leaders in finite time. Finally, the effectiveness of the control protocol designed in this article is verified by numerical simulation.

Distributed Model-Free Adaptive Control for Learning Nonlinear MASs Under DoS Attacks

This article addresses the distributed model-free adaptive control (DMFAC) problem for learning nonlinear multiagent systems (MASs) subjected to denial-of-service (DoS) attacks. An improved dynamic linearization method is proposed to obtain an equivalent linear data model for learning systems. To alleviate the influence of DoS attacks, an attack compensation mechanism is developed. Based on the equivalent linear data model and the attack compensation mechanism, a novel learning-based DMFAC algorithm is developed to resist DoS attacks, which provides a unified framework to solve the leaderless consensus control, the leader-following consensus control, and the containment control problems. Finally, simulation examples are shown to illustrate the effectiveness of the developed DMFAC algorithm.

Observer-Based Event-Triggered Containment Control for MASs Under DoS Attacks

This article studies the observer-based event-triggered containment control problem for linear multiagent systems (MASs) under denial-of-service (DoS) attacks. In order to deal with situations where MASs states are unmeasurable, an improved separation method-based observer design method with less conservativeness is proposed to estimate MASs states. To save communication resources and achieve the containment control objective, a novel observer-based event-triggered containment controller design method based on observer states is proposed for MASs under the influence of DoS attacks, which can make the MASs resilient to DoS attacks. In addition, the Zeno behavior can be eliminated effectively by introducing a positive constant into the designed event-triggered mechanism. Finally, a practical example is presented to illustrate the effectiveness of the designed observer and the event-triggered containment controller.

Robust Standard Gradient Descent Algorithm for ARX Models Using Aitken Acceleration Technique

A robust standard gradient descent (SGD) algorithm for ARX models using the Aitken acceleration method is developed. Considering that the SGD algorithm has slow convergence rates and is sensitive to the step size, a robust and accelerative SGD (RA-SGD) algorithm is derived. This algorithm is based on the Aitken acceleration method, and its convergence rate is improved from linear convergence to at least quadratic convergence in general. Furthermore, the RA-SGD algorithm is always convergent with no limitation of the step size. Both the convergence analysis and the simulation examples demonstrate that the presented algorithm is effective.

Switching cluster synchronization control of networked harmonic oscillators subject to denial-of-service attacks

This paper is concerned with the average cluster synchronization control problem of networked harmonic oscillators under denial-of-service (DoS) attacks. Different from some existing DoS attack models that often necessitate specific statistical characteristics, only the worse-case duration bound of the DoS attacks is required during the control design procedure, which represents the least a priori knowledge of realistic DoS attacks. Then, a novel switching cluster synchronization control scheme, which leverages a position-based feedback control protocol under a non-small delay and a position velocity-based feedback control protocol with a small delay, is developed such that the above two control protocols are selected based on the occurrence of the DoS attacks. Via formulating the resultant synchronization system as a switched time-delay system, a complete-type Lyapunov-Krasovskii functional (LKF) method is further proposed to establish sufficient controller design criteria associated with the duration and frequency of attacks for both synchronous and asynchronous DoS attacks among clusters. Furthermore, an iterative algorithm is designed to calculate the control gain matrices by solving a set of nonlinear matrix inequalities (NLMIs). Finally, a multi-vehicle cooperative control system is presented to demonstrate the validity of the proposed control scheme.

Encoding-decoding strategy based resilient state estimation for bias-corrupted stochastic nonlinear systems

This paper is concerned with the resilient state estimation problem for a type of stochastic nonlinear systems, in which the possible dynamical bias is considered that is depicted by a dynamical equation. In pursuit of enhancing the robustness of the propagated data, a binary encoding strategy (BES) is exploited in the binary symmetric channel (BSC). While the random bit errors caused by the channel noise may take place during the propagation of the binary bit string via the memoryless BSC. To characterize the occurrence of the bit errors, a series of Bernoulli distributed random variables is adopted. More specifically, in order to deal with the possible gain fluctuation of the estimator in the execution process, a resilient state estimator is employed. This paper intends to put forward a novel resilient estimation scheme under the BES, which can assure that the estimation error dynamics is exponentially ultimately bounded in mean square. A sufficient criterion is first acquired for the existence of the expected resilient estimator and the estimator parameter is achieved by solving a convex optimization problem. Finally, an illustrative simulation example is provided to verify the validity of the theoretical results.

A resilient outlier-resistant recursive filtering approach to time-delayed spatial-temporal systems with energy harvesting sensors

This paper is concerned with a resilient outlier-resistant recursive filtering problem for a class of time-delayed spatial-temporal systems (STSs) with energy harvesting sensors. We consider a situation that the sensors are able to harvest energy from external environments and consume certain energy when the measurements are transmitted to filters. When the energy of the sensor is insufficient to maintain the normal communication between the sensors and the filters, the measurement will be regarded as missing. For the sake of obtaining a satisfactory filtering performance, the innovations influenced by the measurement outliers is constrained by introducing a saturation function in the filter. Furthermore, the resilient issue of the designed recursive filter is considered to resist the fluctuations of the filter parameters. Under the effects of sensor energy constraints, measurement outliers as well as parameter fluctuations, a resilient outlier-resistant recursive filter is designed where an upper bound (UB) is first obtained on the filtering error covariance (FEC). Then, by resorting to a matrix recursive equation, such a UB is minimized by the filter gain matrix. Finally, we exhibit a numerical example to verify the effectiveness of the proposed resilient outlier-resistant recursive filter scheme for time-delayed STSs.

Dynamic event-triggered resilient state estimation for time-varying complex networks with Markovian switching topologies

This paper addresses a resilient state estimation problem for an array of nonlinear complex networks with switching topologies under the dynamic event-triggered mechanism (ETM). To reduce the unnecessary data delivery, the dynamic ETM is introduced to schedule the data delivery from sensors to estimators. The model of the switched complex networks is established by adopting a Markov chain which is better to reflect the characteristics of practical complex networks. A set of novel estimators is obtained by using the properties of Kronecker product combining with the Lyapunov-Krasovskii method, and some easy-to-check conditions are derived such that the dynamics of state estimation error satisfies the prescribed H_∞ performance index. In addition, the parameters of the designed resilient state estimators can be acquired by solving a series of convex optimization problems. In the end, a simulation example is given to demonstrate the validity of the proposed theoretical results in this paper.

Event-based consensus control for multi-agent systems against joint sensor and actuator attacks

The paper focuses on the observer-based consensus control issue for a class of discrete-time multi-agent systems suffering from the joint actuator and sensor attacks. An event-triggered communication rule with the adaptive threshold update is introduced to reduce the communication burden. A PI-type controller with a finite-time window integral loop is constructed to achieve bounded consensus in the mean-square sense (BCMS). With the help of common properties of Laplace matrices, the closed-loop multi-agent system is converted into an easy-to-analyze pattern. In light of such a pattern, a sufficient condition is derived to realize the desired consensus by the stochastic analysis. Furthermore, the expected gains of the controller and the observer are determined by resorting to matrix inequalities in combination with the cone complementarity linearization algorithm. Finally, a numerical example and a simulation of the platooning vehicle are proposed to illustrate the effectiveness of the proposed control scheme.

Cross-dimensional formation control of second-order heterogeneous multi-agent systems

This paper is concerned with the cross-dimensional formation control of a second-order multi-dimensional heterogeneous multi-agent system. Agents are first separated into several groups according to their position/velocity vector dimensions. Then the cross-dimensional formation control problem is formulated such that agents in the same group form a time-varying formation in their own dimension and agents in different groups cooperatively move in multiple dimensions. This can make follower agents in different dimensions cooperatively track a leader. Moreover, a cross-dimensional formation protocol is designed based on full or partial information of neighboring agents. For higher-dimensional agents, full information of lower-dimensional neighbors is adopted. For lower-dimensional ones, only partial information of higher-dimensional neighbors is used. Furthermore, a necessary and sufficient condition for the second-order heterogeneous multi-agent system to achieve cross-dimensional formation is provided. Accordingly, a criterion for designing cross-dimensional formation protocol is further derived. Finally, under an undirected graph, a lower-dimensional protocol design criterion is obtained if there is no data exchange between lower- and higher-dimensional followers. The effectiveness of the obtained results is demonstrated through cross-dimensional target enclosing performance analysis for multiple robots and quadrotors.

Recursive state estimation for a class of nonlinear uncertain coupled complex networks subject to random link failures and packet disorders

This paper is concerned with the recursive state estimation (RSE) problem under minimum mean-square error sense for a class of nonlinear complex networks (CNs) with uncertain inner coupling, random link failures and packet disorders. Firstly, a set of random variables obeying the Bernoulli distribution is adopted to characterize whether there are connections between different network units, i.e., there is no random link failure when the random variable is equal to 1, otherwise the random link failure occurs. In addition, the inner coupling strength is assumed to be varying within a given interval and the phenomenon of packet disorders caused by the random transmission delay (RTD) is also taken into account. In our study, the nonlinearity satisfies the continuously differentiable condition, which can be linearized by resorting to the Taylor expansion. The focus of the addressed RSE problem is on the design of an RSE approach in the mean-square error sense such that, for all uncertain inner coupling, random link failures and packet disorders, a suboptimal upper bound of the state estimation error covariance is obtained and minimized by parameterizing the state estimator gain with explicit expression form. Furthermore, a sufficient condition with respect to the uniform boundedness of state estimation error in mean-square sense is elaborated. Finally, a numerical experiment is introduced to demonstrate the validity of the presented RSE approach.

Secure predictor-based neural dynamic surface control of nonlinear cyber-physical systems against sensor and actuator attacks

This paper addresses a secure predictor-based neural dynamic surface control (SPNDSC) issue for a cyber-physical system in a nontriangular form suffering from both sensor and actuator deception attacks. To avoid the algebraic loop problem, only partial states are employed as input vectors of neural networks (NNs) for approximating unknown dynamics, and compensation terms are further developed to offset approximation errors from NNs. With introduction of nonlinear gain functions and attack compensators, adverse effects of an intelligent adversary are alleviated effectively. Furthermore, we present stability analysis and prove the ultimate boundedness of all signals in the closed-loop system. The effectiveness of the proposed control strategy is illustrated by two examples.

Fault tolerant consensus control of multi-agent systems under dynamic event-triggered mechanisms

In this paper, the fault-tolerant consensus control (FTCC) problem is studied for multi-agent systems (MASs) with the dynamic event-triggered mechanism (DETM). To ease the communication burden, DETM governed by an additional internal dynamical variable is introduced. A novel fault-tolerant controller is presented to mitigate system performance degradation caused by failures, where a simple fault compensator is constructed through a protocol-based observer. Then, some sufficient conditions are established to examine the bounded consensus while optimizing the predetermined quadratic cost criterion. In addition, the explicit expression of the desired controller is also parameterized through orthogonal decomposition. Finally, two simulation results are made for the sake of verifying the effectiveness of the developed FTCC scheme, the fault compensation test as well as the quadratic cost one.

Privacy-preserving state estimation with unreliable channels

A co-design problem of privacy-preserving encoding and filtering is concerned in this paper. A remote legal user estimates states of a dynamic system by the received innovation messages. However, the communication channel is neither reliable nor secure. The messages may be missing during the transmission and have a risk of being intercepted by an eavesdropper. Therefore, in this work, an encoding scheme together with an MMSE estimation algorithm are designed for preserving information privacy and meanwhile guaranteeing estimation performance. We introduce a novel encoding approach using a weighted innovation with a public key to achieve privacy security as well as low computational expense. A filtering algorithm is designed under such an encoding mechanism. And the performance of the filter and the encoding method is analyzed. The feasibility of the encoding approach and the filtering algorithm is illustrated through numerical examples of an unstable system and a stable ballistic roll rate estimation system.

Sensor fault detection and minimum detectable fault analysis for dynamic point-the-bit rotary steerable system

In this paper, the sensor fault detection problem considering the drilling disturbances is studied for the dynamic point-the-bit rotary steerable system. Firstly, the DPRSS is modeled as a linear system with the drilling disturbances, including unknown inputs, measurement noises, and model perturbations. Then, a finite-frequency zonotopic fault detection observer is proposed. The finite-frequency range H_- performance and the P-radius criterion are considered to design the observer gains such that the residuals are sensitive to sensor faults and robust against the drilling disturbances simultaneously. Subsequently, the calculation method of minimum detectable faults is presented for the proposed sensor fault detection mechanism. Finally, simulations and experiments are presented to illustrate the effectiveness of the proposed methods.

A switching event-triggered resilient control scheme for primary and secondary levels in AC microgrids

In microgrid hierarchical control, primary control to stabilize system and secondary control to eliminate frequency/voltage deviations are both necessary for islanded microgrids. In this paper, a switching event-triggered (SET) resilient control scheme for microgrid primary and secondary levels has been proposed. First, droop control and model predictive control (MPC) are used for power sharing and driving signal generation respectively on primary level. An SET control method to trigger different MPC cost functions is proposed to balance output voltage quality and switching frequency. Then, distributed consensus and pinning control based method is used on secondary level. An SET mechanism to dynamically adjust secondary ratios to coordinate the transient deviation and response speed is proposed. Next, to deal with severe accidents, a resilient control scheme integrating primary and secondary levels is designed to maintain the system sound operation and improve the system immunity. Finally, the effectiveness of the proposed control scheme has been demonstrated by simulation with comprehensive scenarios.

Distributed Estimation for Stochastic Hamiltonian Systems With Fading Wireless Channels

This article introduces a distributed estimator design problem for the stochastic Hamiltonian systems under fading wireless channels. The phenomenon that the channel outputs are related to the target state and the estimation of the adjacent state is considered to facilitate the implementation of distributed state estimation. Furthermore, the fixed undirected graph simplifies the analysis of the system. By resorting to fading channels and the graph theory, the main goal of the addressed problem is to design estimators to estimate the target state of the Hamiltonian system and guarantee the exponential stability in the mean-square sense of the estimation system. Based on the stochastic analysis method and the structural properties of the Hamiltonian system, sufficient conditions are obtained for the existence of the designed estimator gain for each sensor. Two examples are given to indicate the effectiveness of the theoretical claim.

Distributed Maximum Correntropy Filtering for Stochastic Nonlinear Systems Under Deception Attacks

This article focuses on the distributed maximum correntropy filtering issue for general stochastic nonlinear systems subject to deception attacks. The considered nonlinear functions consist of a determined one and a stochastic one, and the stochastic signals sent by deception attacks with identified statistic characteristics could be non-Gaussian. The corresponding calculation formulas of both the filter gains and the upper bound of the filter error covariance are proposed by means of the Taylor series expansion and the fixed-point iterative update rule, where the weighted maximum correntropy criterion is utilized to take the place of traditional minimum covariance indexes. Such an upper bound is only dependent on the local information, neighbor information, and the identified statistics of deception attacks and, therefore, the developed filtering scheme realizes the requirement of distributed calculation. Furthermore, a simplified version is obtained by removing weights in the correntropy criterion. Finally, an illustrative example is given to verify the effectiveness of developed distributed maximum correntropy filtering subject to deception attacks.

Received Signal Strength Indicator-Based Indoor Localization Using Distributed Set-Membership Filtering

Most of the existing localization schemes necessitate a priori statistical characteristic of measurement noise, which may be unrealistic in practical applications. This article addresses the problem of indoor localization by implementing distributed set-membership filtering based on a received signal strength indicator (RSSI) under unknown-but-bounded process and measurement noises. First, the transmit power and the path-loss exponent are estimated by a novel least-squares curve fitting (LSCF) method in RSSI-based localization. Since the localization process of trilateration is susceptible to inaccuracy caused by the noise-affected distance measurements, a convex optimization method is then developed to obtain the state ellipsoid estimation under the unknown-but-bounded noises. Third, a recursive algorithm is established to compute the global ellipsoid that guarantees to locate the true target at every time step. Finally, experimental validation is presented to demonstrate the accuracy and effectiveness of the proposed set-membership filtering method for indoor localization.

Distributed Event-Based Control for Thermostatically Controlled Loads Under Hybrid Cyber Attacks

In building-microgrid communities, renewable generation and time-varying load usually cause power fluctuations, which influence the ancillary support to the main grid. Thermostatically controlled loads (TCLs) can be utilized to compensate such power variations due to their aggregated and controllable power consumptions. Meanwhile, one basic requirement for the users' side of TCLs is to realize the fair sharing of power states and comfort states. This article proposes a distributed event-based control strategy, where information of neighboring TCLs is exchanged only when a dynamic event-triggered condition is satisfied, and thus it intelligently determines the necessary transmission frequency to save communication resources. From a cybersecurity perspective, the communication network of TCLs may be subject to hybrid attacks, for example, denial-of-service (DoS) and false data-injection (FDI) attacks. During DoS attack intervals, no information can be communicated even through the event-triggered condition is satisfied. Furthermore, the control inputs may also be tampered by FDI attacks. By utilizing the Lyapunov stability and hybrid control theories, sufficient conditions regarding the attack parameters are derived such that fair sharing of power states and comfort states of all involved TCLs can be achieved exponentially. The exclusion of Zeno behaviors is proved and a corollary for ideal communication situations is also deduced. Finally, simulation examples with various attack parameters are conducted to verify the effectiveness of the main results.

Finite-Horizon H∞ Bipartite Consensus Control of Cooperation-Competition Multiagent Systems With Round-Robin Protocols

This article focuses on the finite-horizon H_∞ bipartite consensus control problem for a class of discrete time-varying cooperation-competition multiagent systems (DTV-CCMASs) with the round-robin (RR) protocol. The cooperation-competition relationship among agents is characterized by a signed graph, whose edges are with positive or negative connection weights. Specifically, a positive weight corresponds to an allied relationship between two agents and a negative one means an adversary relationship. The data exchange between each agent and its neighbors is orchestrated by an RR protocol, where only one neighboring agent is authorized to transmit the data packet at each time instant, and therefore, the data collision is prevented. This article aims to design a bipartite consensus controller for DTV-CCMASs with the RR protocol such that the predetermined H_∞ bipartite consensus is satisfied over a given finite horizon. A sufficient condition is first established to guarantee the desired H_∞ bipartite consensus by resorting to the completing square method. With the help of an auxiliary cost combined with the Moore-Penrose pseudoinverse method, a design scheme of the bipartite consensus controller is obtained by solving two coupled backward recursive Riccati difference equations (BRRDEs). Finally, a simulation example is given to verify the effectiveness of the proposed scheme of the bipartite consensus controller.

Optimal Stealthy Deception Attack Against Cyber-Physical Systems

This paper studies the problem of designing the optimal deception attack to maximize a utility function with the Kullback-Leibler divergence adopted as a detection constraint. The utility function reflects the goal of pulling the state away from the origin, increasing the cost of the controller and decreasing the cost of the attacker. To analyze the stealthiness of the attack, the attack signal is decomposed into two parts, one of which is strict stealthy. The necessary and sufficient condition is derived for the case that the strict stealthy attack cannot lead to an unbounded benefit. In this case, the linear transformation of the optimal attack is proved to be a Gaussian distribution. With the mean value and covariance of the Gaussian distribution as variables, the original problem is transformed into a new problem which may not be convex. A suboptimal attack policy is provided and the upper bound for the loss of benefit when using the suboptimal attack is also given. A numerical example of unmanned ground vehicle is illustrated to verify the effectiveness of the proposed attack policy.