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In this paper, considering two typical attack strategies of a DoS jammer, a new kind of H∞ control problem is studied for Cyber-Physical Systems (CPSs) with different transmission mechanism encountering DoS jamming attacks. By defining a concept of working subcycle, the concrete attack strategies of a DoS jammer can be generated by choosing different reasonable value combinations in a unified framework according to the DoS jammer's energy efficiency and stealthiness. Then, for two different transmission mechanisms, namely the time-triggered mechanism (TTM) and the event-triggered mechanism (ETM), in which CPSs can employ in its wireless channels, two DoS jammers employ different attack strategies and launch SINR-based DoS jamming attacks to decrease the quality of wireless communication. Considering the case that the CPSs do not know the DoS jammers' attack strategies, the corresponding H∞ observer-based controllers are designed by using an attack-tolerant mechanism to achieve the desired H∞ disturbance attenuation level, and the controller design problems are transformed to auxiliary convex optimization problems. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed H∞ control methods and the varying of system performance under different interference power chosen by the DoS jammers.

In order to save the usage of system resources and adapt the variation of plant state, this study first proposes a novel stochastic-sampling-based adaptive event-triggered scheme (AETS). Second, in the framework of time-delay systems, the closed-loop control system is modelled as a class of delayed stochastic systems where time-delay is distributed in some intervals with probability. Then, by employing stochastic analysis tool and Lyapunov stability theory, a stability criterion for this class of delayed stochastic systems is established to ensure that the system possesses stochastically asymptotic stability with an H ∞ disturbance attenuation performance. Also, a co-design of parameter matrices of the state-feedback controller and the stochastic-sampling-based AETS is implemented. Third, based on the obtained co-design condition, a convex optimisation algorithm for the tradeoffs between disturbance attenuation performance and resource utilisation of the closed-loop control system is further developed. Finally, the effectiveness and feasibility of the proposed control strategy are illustrated by two numerical examples of adaptive event-triggered control for networked control systems under stochastic sampling.

In this paper, the H∞ control problem for a class of linear time-varying cyber-physical system (CPS) under randomly occurring hybrid attacks in a finite horizon is investigated. The hybrid attacks, including denial of service (DoS) attacks on both sensor-to-controller and controller-to-actuator communication channels and false data injection (FDI) attacks on sensors and actuators, aim to destroy the measurement data and control data in order to endanger the functionality of the closed-loop system. The purpose of this paper is to study the relationship between the attack injected signals and the controlled output, and to design the output feedback controller gains so that the H∞ performance of the closed-loop system is guaranteed over a given finite horizon, meanwhile, the impact of attack signals in the worst case on the linear quadratic performance can be reduced. In order to solve the above problems, both the methods of stochastic analysis and completing squares are utilized to establish the sufficient conditions for the existence of the desired controller, and a finite-horizon controller design algorithm is presented by solving two coupled backward recursive Riccati difference equations (RDEs) subject to some scheduled conditions. At last, the numerical simulation and experimental results are given out to demonstrate the effectiveness of the proposed approach.

This paper investigates the distributed consensus problem for heterogeneous multi-agent systems via event-triggered scheme. To alleviate the communication burden, a distributed event-triggered consensus algorithm using an open-loop estimate and neighboring information is proposed. In the proposed event-triggered scheme, the control input of each agent is dependent on the estimate and information at discrete instants. Firstly, the novel event-triggered consensus algorithm is proposed for fixed topology, which involves the discrete communication between neighboring agents. Then, for the switching topology, the triggering condition is proposed by virtue of a topology-dependent dwell time approach. Further, the corresponding consensus procedures are given. Finally, the effectiveness of the proposed scheme is illustrated by numerical results.

This paper focuses on the data-driven optimal attack strategy against state estimation in cyber-physical systems (CPSs). Different from the research on attack strategies of specific attack types, the proposed attack strategy addresses the optimal selection of attacked targets, which can combine with different attack types and produce greater threats to CPS. In particular, a causality analysis (CA) on the measurement data is first proposed to evaluate the significance of nodes (sensor groups) and help the implementation of the optimal node attack, since the system topology and parameters are not available to adversaries. On the one hand, a multivariate transfer entropy and several data preprocessing methods are employed to complete the CA between sensor groups qualitatively. On the other hand, three new indexes, e.g., driver degree, are defined to complete the CA quantitatively. Moreover, the theoretical basis for the proposed node attack is provided, in which the superiority of the node attack is proven from the view of observability. Finally, the case studies on the smart grid are illustrated to verify the superiority of the proposed attack strategy.

The additional threshold of a mixed event-triggering mechanism (ETM) makes it impossible to guarantee the requirement of asymptotic stability. As a consequence, it is necessary to investigate input-to-state practically stable (ISpS) which is a mild stability property. In this study, the authors firstly model the closed-loop event-triggered control system as a delayed linear parameter-varying (LPV) systems with a mixed ETM and parameter uncertainty. Then, a co-design condition in a sense of ISpS of controller gain and trigger parameters for the delayed LPV systems is obtained by employing the parameter-dependent Lyapunov–Krasovskii functionals and congruent transformation method. Moreover, based on the obtained co-design condition in a sense of ISpS, an optimisation algorithm for the tradeoffs between resource utilisation and robustness of the closed-loop system is further proposed. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed method.

In this paper, considering two typical attack strategies of a DoS jammer, a new kind of H

This paper investigates the robust control method for networked dynamic systems and its application for a direct-drive linear motion control system in a network environment. The unavoidable network-induced random delays are modeled as Markov chains. The control object of the linear motion control system in this study is a double-sided linear switched reluctance machine (DLSRM). To tackle the inherent uncertainties in the DLSRM, a robust control strategy is designed by proposing a new Lyapunov function and applying the free-weighting matrix technique. A state feedback robust controller is designed such that the closed-loop direct-drive linear motion control system over a network is stochastically robust stable. The robust controller can be conveniently obtained by solving a set of linear matrix inequalities. The numerical simulation of an angular positioning system is presented to illustrate the effectiveness of the proposed robust control method. Furthermore, the experimental tests on the networked direct-drive linear motion control system verify the practicability of the proposed method.

The problem of robust stochastic stability and delayed-state-feedback stabilisation of uncertain Markovian jump linear systems with random Markov delays is investigated. Based on the Lyapunov stability theory and robust analysis techniques, some robust stochastic stability criteria are derived in terms of linear matrix inequalities. Robust delayed-state-feedback controllers that stochastically stabilise the uncertain Markovian jump linear systems is also proposed. The state variable on the controller is assumed to be dependent on the Markov delay that has uncertain transition probabilities. Finally, numerical examples are provided to illustrate the feasibility and effectiveness of the proposed methods.

This paper focuses on the robust output feedback $\mathscr {H}_{2}/\mathscr {H}_\infty $ control issue for a class of discrete-time networked control systems with uncertain parameters and external disturbance. Sensor-to-controller and controller-to-actuator packet dropouts and time delays are considered simultaneously. According to the stochastic characteristic of the packet dropouts and time delays, a model based on a Markov jump system framework is proposed to randomly compensate for the adverse effect of the two-channel packet dropouts and time delays. To analyze the robust stability of the resulting closed-loop system, a Lyapunov function is proposed, based on which sufficient conditions for the existence of the $\mathscr {H}_{2}/\mathscr {H}_\infty $ controller are derived in terms of linear matrix inequalities, ensuring robust stochastic stability as well as the prescribed $\mathscr {H}_{2}$ and $\mathscr {H}_\infty $ performance. Finally, an angular positioning system is exploited to demonstrate the effectiveness and applicability of the proposed design strategy.

This study studies coordinated control of a platoon of vehicles consisting of a leader and multiple followers when multiple vehicles suffer from disturbances. Small disturbances acting on one vehicle may cause large spacing errors between intervehicles. In addition, the spacing errors propagate up or down in a vehicle platoon. To mitigate the adverse effect of the disturbances, a control law is proposed based on only the position information of the vehicle itself and its preceding vehicle. To analyse the disturbances propagation among the platoon, the upper bounds of two transfer functions are presented including the transfer function matrix 𝒢 de from external disturbances to spacing errors as well as the transfer function matrix 𝒢 ue from a leader's input control to spacing errors. Furthermore, an alternative control law is proposed when the velocity of the leader is known by the followers. In this case, two tighter upper bounds of 𝒢 l de and 𝒢 l ue are presented. The derived upper bounds of the transfer functions are independent of the number of vehicles in the platoon. Simulations verify the effectiveness of the proposed approach.

A new generalised Kalman filtering algorithm using a multiplicative measurement noise model is developed for tracking moving targets in a wireless sensor network. This multiplicative error model facilitates more accurate characterisation of the distance dependence measurement errors of range-estimating sensors. Two new formulations of extended Kalman filter (EKF) and unscented Kalman filter (UKF), called generalised EKF (GEKF) and generalised UKF (GUKF) are derived. Comparing with conventional EKF and UKF formulations, it is shown that GEKF and GUKF can achieve smaller tracking error than traditional EKF and UKF. Simulation results are also reported that demonstrated the superior performance of GEKF and GUKF over existing methods.

A new approach to solving the distributed control problem for a class of discrete-time nonlinear systems via a wireless neural control network (WNCN) is presented in this paper. A unified Lurie-type model termed delayed standard neural network model (DSNNM) is used to describe these nonlinear systems. We assume that all neuron nodes in WNCN which have limited energy, storage space, and computing ability can be regarded as a subcontroller, then the whole WNCN is characterized by a mesh-like structure with partially connected neurons distributed over a wide geographical area, which can be considered as a fully distributed nonlinear output feedback dynamic controller. The unreliable wireless communication links within WNCN are modeled by fading channels. Based on the Lyapunov functional and the S-procedure, the WNCN is solved and configured for the DSNNM to absolutely stabilize the whole closed-loop system in the sense of mean square with aH∞disturbance attenuation index using LMI approach. A numerical example shows the effectiveness of the proposed design approaches.

Wireless sensor and actuator networks combine a large number of sensors and a lower number of actuators that are connected with wireless medium, providing distributed sensing and executing appropriate tasks in a special region of interest. To accomplish effective sensing and acting tasks, efficient coordination mechanism among the nodes is required. As an attempt in this direction, this paper develops a collaborative control and estimation mechanism, which addresses the nodes coordination in a distributed manner. First, we propose a regional controllability-based virtual force algorithm as an actuator deployment strategy to enhance area coverage after an initial random placement of actuators. During this process, a dynamic coordination mechanism is adopted to control nodes. This mechanism incorporates two components, namely, proportional-integral-derivative neural network and recursive least squares-based Kalman filter algorithms. Taking advantage of feedback control and online learning technology, the proposed coordination mechanism schedules the corresponding nodes on the basis of the characteristics of current events, utilizes proportional-integral-derivative neural network controller inside each actuator to improve system transient and steady-state responses, and deals with system state/parameter estimation problems according to the recursive least squares-based Kalman filter algorithm, so as to achieve better control accuracy. Simulations demonstrate the effectiveness of our proposed methods. Copyright © 2013 John Wiley & Sons, Ltd.

Wireless sensor and actuator network (WSAN) is a new generation of wireless sensor network (WSN) and has been widely used in various applications. WSANs are not only able to monitor physical environment, but also to change the environment by appropriate action. This paper presents a typical WSAN application: a collaborative control system for intelligent lighting based on an illuminance distribution model. The system focuses on meeting human illuminance and human uniformity requirements simultaneously as far as possible. To reach the goal, a collaborative control method including collaborative sensing and collaborative actuation is used. In the process of calculating the control signals, a simple yet efficient gradient descent algorithm is applied. Simulation is implemented to verify the effectiveness of our design.

The problem of distributed estimation of an unknown noise-corrupted parameter in wireless sensor networks, with a fusion centre, is considered. Convolutional coding and rate-compatible punctured convolutional coding are used to protect the transmission of sensor observations and to reduce the impact of noise channels. Two novel kinds of power scheduling based on different encoding methods are derived for minimising the total power consumption. The formulas of the proposed power scheduling suggest that local sensors with poor observation qualities should decrease their quantisation levels. The levels should also be related to coding methods, channel qualities, a given mean squared error (MSE) and local signal-to-noise ratios. Finally, simulation results show that not only these two schemes are energy-efficient but also they can achieve comparable performance of a given MSE.

The problem of estimating an unknown parameter in wireless sensor networks with a fusion centre (FC) is studied. Each sensor observation is quantised as a result of the bandwidth constraint and then each quantised observation is transmitted to the FC over a binary symmetric channel (BSC). Under this setting, some estimators have been proposed but the maximum likelihood estimator (MLE) as well as the impact of the parameters of BSCs on the estimation performance are rarely considered. Assuming that the same one-bit quantiser is adopted at every sensor, the MLE and the Cramer - Rao lower bound (CRLB) are derived based on the quantised observations transmitted over BSCs. The impact of the capacity and the crossover probability of BSCs on the performance of the MLE and the CRLB are highlighted. The results reveal that the capacity of BSCs greatly influences both the performance of the MLE and the CRLB. It is also shown that both the performance of the MLE and the CRLB have the symmetric property with respect to the crossover probability of BSCs.

Packet losses are a general problem in networked control system and wireless sensor networks (WSNs). In order to increase estimation accuracy and reliability, a filter with finite packet losses called minimum variance filter (MVF) is designed for stochastic systems. The authors develop a packet loss model, and design a novel MVF based on the orthogonal analysis approach. The proposed filters rely only on the packet arrival probability at each time instant and do not need to know whether the measurement is received at a particular time instant. However, the proposed MVF is not applicable to non-linear cases. So an extended MVF is derived for stochastic non-linear systems and applied to track a moving target in WSNs. Simulation results show that, compared to existing methods, the proposed MVFs have superior performance.

A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the master and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay-jitter, a new data buffer scheme is performed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of teleoperation. The usefulness and effectiveness of the proposed method and system are proven by teleoperation experiments via the internet over a long distance.

Decentralized robust stabilization problem of discrete-time fuzzy large-scale systems with parametric uncertainties is considered. This uncertain fuzzy large-scale system consists of N interconnected T-S fuzzy subsystems, and the parametric uncertainties are unknown but norm-bounded. Based on Lyapunov stability theory and decentralized control theory of large-scale system, the design schema of decentralized parallel distributed compensation (DPDC) fuzzy controllers to ensure the asymptotic stability of the whole fuzzy large-scale system is proposed. The existence conditions for these controllers take the forms of LMIs. Finally a numerical simulation example is given to show the utility of the method proposed.

New delay-independent and delay-dependent stability criteria for linear systems with multiple uncertain delays are established by using both the time-domain and the frequency-domain methods. The results are derived based on the established new preliminary lemmas and by using new-type stability theorems for general retarded dynamical systems and new analysis techniques in the time-domain and the frequency-domain. All the established stability criteria depend only on the eigenvalues related to the coefficient matrices of the systems and do not involve any free tuning parameters. In addition, some remarks are given to explain in detail the obtained results and to point out the limitations of the existing results in the literature.

This paper has two purposes. One is to establish new stability criteria for linear systems with multiple time-varying/constant delays, and the other is to point out the limitations of the author's previous results. The stability criteria, including delay-dependent and delay-independent ones, are derived by using both time-domain and frequency-domain techniques. All of the established stability criteria are given in the form of linear matrix inequality problems, including only one tuning parameter matrix P > 0 ∈ R n × n .

Four new stability theorems for general classes of retarded dynamical systems are established by using the Lyapunov function approach in this paper. A new technique is proposed for estimating the derivative of the Lyapunov function along the solution of a system at some specific instant. It is remarked that the stability conditions obtained by the established stability theorems together with the proposed technique are less conservative than those obtained by the existing Razumikhin-type theorems and techniques in the literature. Four illustrative examples and two corollaries for systems with a single time-varying delay or multiple time-varying delays are given to show the applications of the established stability theorems and the proposed technique.

Two new asymptotic stability criteria for linear time-invariant systems with multiple delays are established by using a quadratic inequality lemma together with frequency-domain techniques. One criterion is for delay-dependent α-stability and another is for delay-independent asymptotic stability. Each of them has only one tuning parameter matrix P>0 as the Lyapunov-type stability criteria for the corresponding linear time-invariant systems without delays do. Both of the established stability criteria are given in the form of LMI problems and hence are very easy to use in applications. In addition, it is remarked that the established delay-independent asymptotic stability criterion with one tuning parameter matrix P>0 improves and simplifies the existing criterion with more than one tuning parameter matrix in the literature.

In this paper, automatic motion control is investigated for one of wheeled inverted pendulum (WIP) models, which have been widely applied for modeling of a large range of two wheeled modern vehicles. First, the underactuated WIP model is decomposed into a fully actuated second order subsystem Σa consisting of planar movement of vehicle forward and yaw angular motions, and a nonactuated first order subsystem Σb of pendulum motion. Due to the unknown dynamics of subsystem Σa and the universal approximation ability of neural network (NN), an adaptive NN scheme has been employed for motion control of subsystem Σa . The model reference approach has been used whereas the reference model is optimized by the finite time linear quadratic regulation technique. The pendulum motion in the passive subsystem Σb is indirectly controlled using the dynamic coupling with planar forward motion of subsystem Σa , such that satisfactory tracking of a set pendulum tilt angle can be guaranteed. Rigours theoretic analysis has been established, and simulation studies have been performed to demonstrate the developed method.

This paper considers a leader-following tracking control problem for second-order multiagent systems (MASs) under measurement noises and directed communication channels. It is assumed that each follower-agent can measure the relative positions and velocities of its neighbors in a noisy environment. Based on a novel velocity decomposition technique, a neighbor-based control law is designed to realize local control strategies for these continuous-time agents. It is shown that the proposed consensus protocol can guarantee that all the follower-agents track the active leader. In addition, this result is extended to a more general case with switching topologies. Finally, a numerical example is given for illustration.

Energy efficient collaborative target tracking in a wireless sensor network (WSN) is considered. It is assumed that the distance estimates of range sensors are contaminated by distance-dependent multiplicative observation noises. The nonlinear measurement model leads to the application of a generalized unscented Kalman filtering (GUKF) tracking algorithm. Energy efficient operation is achieved by imposing an energy balance criterion to select a subset of sensors near the target to participate in collaborative tracking without compromising tracking performance. This is formulated as a multiobjective constrained optimization problem that minimizes both the state covariance of the GUKF algorithm and the variance of on-board residue energy of sensor nodes within the detection range of the target. An efficient, distributed, polynomial time heuristic algorithm that achieves a performance close to the optimal solution is proposed. Extended simulation results indicate that this proposed joint scheduling and tracking algorithm is capable of delivering desired tracking performance while significantly extending the WSN lifespan.

This paper is concerned with the problem of modeling and output feedback controller design for a class of discrete-time networked control systems (NCSs) with time delays and packet dropouts. A Markovian jumping method is proposed to deal with random time delays and packet dropouts. Different from the previous studies on the issue, the characteristics of networked communication delays and packet dropouts can be truly reflected by the unified model; namely, both sensor-to-controller (S-C) and controller-to-actuator (C-A) time delays, and packet dropouts are modeled and their history behavior is described by multiple Markov chains. The resulting closed-loop system is described by a new Markovian jump linear system (MJLS) with Markov delays model. Based on Lyapunov stability theory and linear matrix inequality (LMI) method, sufficient conditions of the stochastic stability and output feedback controller design method for NCSs with random time delays and packet dropouts are presented. A numerical example is given to illustrate the effectiveness of the proposed method.

A new criterion for delay-independent stability of linear large scale time-delay systems is deduced by employing an improved Razumikhin-type theorem and the m-matrix properties. An illustrative example is given to demonstrate the superiority of the obtained results to those in the literature. >

This paper is concerned with a containment problem of networked fractional-order system with multiple leaders under a fixed directed interaction graph. Based on the neighbor rule, a distributed protocol is proposed in delayed communication channels. By employing the algebraic graph theory, matrix theory, Nyquist stability theorem, and frequency domain method, it is analytically proved that the whole follower agents will flock to the convex hull which is formed by the leaders. Furthermore, a tight upper bound on the communication time-delay that can be tolerated in the dynamic network is obtained. As a special case, the interconnection topology under the undirected case is also discussed. Finally, some numerical examples with simulations are presented to demonstrate the effectiveness and correctness of the theoretical results. Published version

International audience; In this paper, the sensor data is transmitted only when the absolute value of difference between the current sensor value and the previously transmitted one is greater than the given threshold value. Based on this send-on-delta scheme which is one of the event-triggered sampling strategies, a modified fault isolation filter for a discrete-time networked control system with multiple faults is then implemented by a particular form of the Kalman filter. The proposed fault isolation filter improves the resource utilization with graceful fault estimation performance degradation. An illustrative example is given to show the efficiency of the proposed method.

An improved Razumikhin-type theorem is established, and the advantage of the established theorem for reducing conservatism is discussed. For a class of time-delay systems, a simple asymptotic stability condition is deduced as an application of the established theorem. Two illustrative examples are given to show the superiority of the results to those in the literature. >

In wireless sensor and actuator networks (WSANs), the sensor nodes are involved in gathering information about the physical phenomenon, while the actuator nodes take decisions and then perform appropriate actions upon the environment. The collaborative operation of sensor and actuator nodes brings significant advantages over WSNs, including improved accuracy and timely actions upon the sensed phenomena. However, unreliable wireless communication and finding a proper control strategy cause challenges in designing such network control system. In order to accomplish effective sensing and acting tasks, efficient coordination mechanisms among different nodes are required. In this paper, the coordination and communication problems in WSANs are studied. First, we formulate the mathematical models for the WSANs system. Then, a predictor-controller algorithm based on distributed estimation is adopted to mitigate the effects of network-induced delay. Finally, we apply a collaborative processing mechanism to meet the desired system requirements and improve the overall control performance. This approach will group the sensor and actuator nodes to work in parallel so as to reduce the computation complexity and enhance the system reacting time. Simulation results demonstrate the effectiveness of our proposed method.

Xu and Liu (see ibid., vol.39, no.4, p.839-41, 1994) tried to improve the well-known Razumikhin theorem on the stability of differential functional equations. The commenter states that, the proof of their main result contains an error, so the results may not be correct. In reply Bugong Xu gives a corrected result.

States that some expressions in the above paper by Su and Huang (IEEE Trans. Autom. Contr., vol. 37, no. 10, p.1656-59, 1992) should be modified and that there are also errors in the above paper. >