This paper studies the adaptive prescribed-time control problem for the strict-feedback systems with unknown non-smooth nonlinearities. Different from the existing adaptive prescribed-time designs where the nonlinearities are required to be known and smooth, a novel design is developed, for the first time, in the presence of the unknown non-smooth nonlinearities eliminating the need for smoothness or knowledge. Moreover, in the design we suggest a new scaled quadratic Lyapunov function depending on a tuning parameter, which together with the characteristics of the introduced scaling function constructs a state-feedback controller allowing to balance the tradeoff between the transient performance and control effort. As a byproduct of this development, we also provide solutions to prescribed-time control of the strict-feedback nonlinear systems. It should be noted that the designed controller has smaller gains thus with reduced control effort while ensuring the prescribed-time stabilization. Finally, three examples are provided to illustrate the efficiency of the proposed method.

This study proposes an active defense strategy against denial-of-service (DoS) attacks to address the secure event-triggered control of multiarea load frequency control (LFC) systems. A novel interval secure event-triggered mechanism (ISETM) is introduced, integrating event-triggered control with cybersecurity mechanisms under the software defined network (SDN) framework. ISETM generates not only a triggering instant but also a secure triggering interval (STI) simultaneously. The STI sent to the SDN control plane is an estimation time interval generated by the Taylor expansion and model-based prediction method. During this interval, the SDN control plane programs OpenFlow switches to filter attack traffics, ensuring delayed but secure triggering transmission. Under ISETM conditions represented by two systems of inequalities, a multiarea LFC system is modeled as a delay system incorporating a triggering error based on the Taylor expansion. To achieve performance of the established LFC system, a criterion is derived using the Lyapunov-Krasovskii functional method. A codesign approach is provided to solve the proposed ISETM control (ISETC) gains through linear matrix inequality (LMI) techniques. Finally, simulations validate the effectiveness and advantages of our proposed method.

The tracking control problem for strict-feedback systems with unknown dynamics has been extensively studied. However, most existing control approaches require online approximation models and associated a priori assumptions. In order to avoid the necessity of deriving online models, this article proposes a data-driven backstepping control (DBC) approach for a class of strict-feedback systems with unknown dynamics. First, unlike the widely-studied adaptive backstepping control approaches, we identify the unknown dynamics of each subsystem based on off-line data and develop a data-driven continuous-time Lyapunov equation return controller, ensuring semi-global exponential stability of the error system. Furthermore, we propose a data-driven dynamic surface control (DDSC) approach for the "complexity explosion" problem in DBC. This approach uses a data-driven linear matrix inequality to return the controller, ensuring that the error system remains semi-globally ultimately uniformly bounded, even when the derivative of the virtual controller cannot be calculated. Finally, the superiority and effectiveness of DBC and DDSC are verified by simulation examples.

This paper proposes a novel co-design method of denial-of-service (DoS) attack-resilient time varying estimators/observers and controllers aimed at addressing these challenges in a discrete-time linear networked control systems (NCSs) under sensor and actuator false data injection (FDI) attacks. Our time-varying estimators have uniquely equipped to perform a joint estimation of the system state, sensor and actuator attack signals despite the presence of the intermittent DoS attacks. The main features of the developed time-varying observers are twofold: firstly, it involves time-varying gains corresponding to the DoS attack off/on transitions, and secondly, it entails augmenting the estimations of sensor and actuator FDI attacks within the piecewise observer error dynamics, thus providing a comprehensively and rigorous estimation and control methodologies. By introducing the conceptions of minimum and maximum sleeping/active durations of DoS attacks, a new time-varying DoS attack instant-dependent piecewise Lyapunov function approach is proposed to analyze theH∞stability of the augmented estimation error system and closed-loop control system under sensor and actuator FDI attacks. Based on the obtainedH∞stability analysis results, time-varying gains of state and attack observers are formulated to construct the DoS-resilient observers. Besides, the time-varying feedback gains are also obtained to construct the DoS-resilient controllers by attack compensation based on the actuator FDI attack estimations of time-varying observers, thus achieving the mitigation of sensor and actuator FDI attacks. Case studies are performed on a three-area interconnected power systems under DoS and FDI attacks to validate the effectiveness and advantages of the developed theoretical findings.

This article addresses the issue of privacy-preserving distributed economic dispatch in integrated energy systems (IESs). We propose the time-varying inherent privacy-preserving consensus algorithm (TVIPPCA) without involving a third party, aimed at safeguarding sensitive information during communication and ensuring optimal energy provision at minimal cost. The proposed TVIPPCA is designed with inherent privacy protection for each private variable, featuring a two-layer security strategy. The first layer of security is achieved through an intrinsic node decomposition mechanism coupled with random mixing coefficients, effectively shielding key system parameters from potential adversaries. The second layer enhances privacy preservation by designing a time-varying weight matrix strategy, further obfuscating the information transmitted. Through rigorous theoretical analysis, the proposed TVIPPCA is proven to converge to the optimal value while strictly protecting the privacy of sensitive information. Simulations in a 39-32 node IES validate the algorithm's efficacy in cost optimization and privacy protection.

In this article, the stability analysis and synthesis issues of networked control systems with asynchronous sensors and controllers are studied, where the stochastic variable obeying a certain probability distribution is introduced to characterize the clock offset between the sensor and the controller. First, a continuous-time framework covering random clock offsets and consecutively lost packets is established. An appropriate discrete-time stochastic augmented model is then constructed to investigate the analysis and synthesis problems of resulting continuous-time framework. Therefore, we prove that the stochastic stability of the discrete-time model implies the stochastic stability of resulting continuous-time system. Based on the discrete-time stochastic augmented model, the random and highly nonlinear terms are decoupled with the help of the law of total expectation, Kronecker product operation, and reduced-order confluent Vandermonde matrix. Subsequently, we present the stability condition in the form of linear matrix inequality and design the desired gain matrix such that the original continuous-time system is stochastically stable. Finally, two numerical examples and a practical example are utilized to clarify the practicability of the designed strategy.

In this article, the exponential stability (ES) and fuzzy control problem is addressed for DC microgrid (DC-MG) system based on T-S fuzzy model under denial-of-service (DoS) attacks. Considering that the time scale of networked T-S fuzzy model and parallel distributed compensation (PDC) fuzzy control rules is asynchronous, the T-S fuzzy model of the DC-MG system is established. More importantly, in order to reflect the effect of DoS attacks, a time-constrained DoS attack (TCDA) model, which only characterizes the duration of DoS attacks, is established compared with the classic DoS attack model. Then, a switched DC-MG fuzzy system model based on state-feedback control law and TCDA model is established. Furthermore, the time-varying Lyapunov function related to attack parameters is used to ensure the ES of the system. Besides, a fuzzy-dependent switching control strategy is designed in terms of linear matrix inequalities (LMIs). Finally, through a simulation example, the effectiveness of the proposed control strategy is verifiedNote to Practitioners—As a typical example of cyber-physical systems, nonlinear DC-MG system is vulnerable to malicious cyber attacks (such as DoS attack). The existing DoS attack models are usually characterized by the duration and frequency of attacks. In this paper, we adopt a new approach to describe the DoS attack model using only attack duration characteristics. This makes the DoS attack model more general. We then propose a switching fuzzy control algorithm subject to intermittent DoS attacks and derive sufficient conditions for tolerable duration of attack. This can allow practitioners to know under what conditions the ES of the attacked system can still be guaranteed. The effectiveness of theoretical analysis results is verified by simulation experiments. In the future research, we will address the design of fuzzy control algorithms for DC-MG under various cyber attacks.

In this article, the stochastic analysis and$H_{\infty }$controller design problems of networked systems with packet dropouts and false data injection attacks are investigated. Different from the existing literature, we focus on the linear networked systems with external disturbances and both sensor–controller channel and controller–actuator channel are studied. First, we present a discrete-time modeling framework that leads to a stochastic closed-loop system with randomly varying parameters. To facilitate the analysis and$H_{\infty }$control of resulting discrete-time stochastic closed-loop system, an equivalent yet analyzable stochastic augmented model is further constructed by matrix exponential computation. Based on this model, a stability condition is derived in the form of linear matrix inequality (LMI) with the aid of a reduced-order confluent Vandermonde matrix, Kronecker product operation, and law of total expectation. Specifically, the dimension of the LMI obtained in this article does not increase as the upper bound of consecutive packet dropouts does, which is also different from the existing literature. Subsequently, a desired$H_{\infty }$controller is obtained such that the original discrete-time stochastic closed-loop system is exponentially mean-square stable with a prescribed$H_{\infty }$performance. Finally, a numerical example and a direct current motor system are exploited to substantiate the effectiveness and practicability of the designed strategy.

This paper is concerned with a resilient load frequency control (LFC) of multi-area power systems subject to unknown load disturbances and intermittent denial-of-service (DoS) attacks. The central aim is to develop a feasible and less conservative DoS-resilient LFC scheme that constrains jammer’s actions as less as possible and explores available attack information as much as possible in desired analysis and design criteria. Towards this aim, we first present a partially known DoS model that bounds merely the DoS-on durations. We then elaborate a sampled-data-based transmission paradigm which characterizes explicitly the uniform sampling instants and intermittent DoS-on and -off instants as well as the nonuniform arriving instants of the transmitted system data. Furthermore, we develop a novel attack-parameter-dependent Lyapunov functional to establish less conservative conditions for both stability analysis and controller design. It is shown that the exponential stability of the resultant closed-loop LFC system can be guaranteed, while also preserving both the desired minimum sleeping rate of DoS attacks and the prescribedH∞performance index against changing load disturbances. Finally, several case studies of a three-area power system are provided to verify the effectiveness and superiority of the derived theoretical results.

Autonomous vehicles (AVs) are being enhanced by introducing wireless communication to improve their intelligence, reliability and efficiency. Despite all of these distinct advantages, the open wireless communication links and connectivity make the AVs’ vulnerability to cyber-attacks. This paper proposes an$L_{2}$-gain-based resilient path following control strategy for AVs under time-constrained denial-of-service (DoS) attacks and external interference. A switching-like path following control model of AVs is first built in the presence of DoS attacks, which is characterized by the lower and upper bounds of the sleeping period and active period of the DoS attacker. Then, the exponential stability and$L_{2}$-gain performance of the resulting switched system are analyzed by using a time-varying Lyapunov function method. On the basis of the obtained analysis results,$L_{2}$-gain-based resilient controllers are designed to achieve an acceptable path-following performance despite the presence of such DoS attacks. Finally, the effectiveness of the proposed$L_{2}$-gain-based resilient path following control method is confirmed by the simulation results obtained for the considered AVs model with different DoS attack parameters.

This study is concerned with the$H_{\infty }$control issue of networked systems with consecutively lost packets using sampled-data. First, we establish a discrete stochastic system for the networked system with external disturbances and consecutively lost packets. To enable$H_{\infty }$performance analysis, an equivalent but analyzable stochastic framework is then derived by using matrix exponential computation. Subsequently, by law of total expectation, Kronecker product operation, and eigenvalue decomposition approach, we compute the expectation of a coupling term with significant nonlinearity and randomness. Based on this, a stabilization controller is constructed that ensures the resulting discrete stochastic system’s exponential mean-square stability with a prescribed$H_{\infty }$performance. Unlike the existing literature, the linear matrix inequalitys (LMIs) dimension derived in this article does not change along with the maximum number of consecutively lost packets, which prevents an LMI with high-computing complexity. Finally, the validity and applicability of the algorithm are demonstrated by a numerical example and an example using a satellite system.

This article is concerned with resilient adaptive event-triggered$H_{\infty }$fuzzy filtering for a class of interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy-model-based cyber-physical systems (CPSs) under stochastic sampling and energy-constrained, nonperiodic denial-of-service (DoS) attacks. The nonlinear plant with parameter uncertainties is represented as a class of IT2 T–S fuzzy systems, and a novel resilient adaptive event-triggered scheme (AETS) against stochastic sampling and DoS attacks is proposed. In the designing process of the fuzzy filter, a novel resilient switched IT2 T–S fuzzy filter that switches according to the DoS attacks is applied. Then, the switched stochastic delayed systems model with a favorable form is established for the filtering-error-system. Based on the Lyapunov–Krasovskii stability theory and switched stochastic delayed systems theory, the relaxed stability condition is derived, which can ensure that the filtering-error-system is stochastically exponentially stable (SES) where the decay rate is indicated, the maximum frequency of DoS attacks is revealed, and an$H_{\infty }$disturbance attenuation performance is guaranteed. Also, the codesign algorithm is further developed to implement the codesign of fuzzy filter and resilient AETS. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed strategy.

Cyber security of modern power systems has become increasingly significant due to their open communication architecture and expanding network connectivity exposed to malicious cyber attacks. Resilient control represents an effective means to preserve the survivability of the power system under cyber attacks. In this paper, we address the resilient load frequency control (LFC) design for multi-area power systems under a new class of time-constrained denial-of-service (DoS) attacks. First, different from the widely-explored duration- and frequency-constrained DoS attack models, we consider a general time-constrained DoS attack model where only the attack durations are confined into some bounds, which represents less a priori knowledge of an attacker’s actions. Second, instead of using a traditional yet conservative time-invariant Lyapunov function (TILF), we develop an attack-parameter-dependent time-varying Lyapunov function (TVLF) approach to enable a resilient LFC design without jeopardizing the desired closed-loop system stability and performance. Furthermore, we provide a formal stability and performance analysis condition as well as a design criterion for the desired DoS-resilient output feedback LFC controller. We also show that the minimum allowable sleeping period and the maximum allowable active period of the attacked LFC system can be explicitly disclosed. Finally, we present two simulation case studies on a two-area LFC system and a three-area LFC system to demonstrate the effectiveness of the obtained results.

This article discusses a control problem of underactuated autonomous surface vehicles (ASVs) subject to internal/external uncertainties, input saturations, and actuator faults, and proposes a novel event-triggered adaptive PID fault-tolerant (ETAPID-FT) control solution. To resolve the design difficulty caused by the underactuated feature, a standard multivariate integral cascade form regarding the mathematical model of underactuated ASVs is established. And then, to facilitate the implementation of PID-based design framework, the nonsmooth actuator saturation nonlinearity caused by the saturation constraint is represented by a smooth saturation model. In the control design, considering full features of the actuator fault and smooth function, an indirect neural approximation with single-parameter-leaning technique is developed, which endows the function of self-tuning control gain for the control solution. To relieve the mechanical wear of actuator, an improved event-triggered protocol by implanting a decreasing function of ASV’s position error is proposed. Moreover, the theoretical results show that the proposed ETAPID-FT control solution can guarantee the boundedness of all the signals in the closed-loop control system of underactuated ASVs. Finally, the validity of the developed control solution is confirmed by the simulation and comparative results

This article is concerned with attack-resilient event-triggered$H_{\infty }$filtering for a class of networked nonlinear systems described by an interval type-2 (IT2) fuzzy model. Suppose that data transmission from the plant to the filter is completed through a wireless sensor network subject to denial-of-service attacks (DoS). In order to save the limited network bandwidth and resist the effects of DoS attacks, a resilient event-triggered communication scheme is devised. Then, an attack-resilient IT2 filter model is introduced to estimate system states of the nonlinear plant. Based on a piecewise Lyapunov–Krasovskii functional, sufficient conditions are obtained to ensure that the filtering error system is exponentially stable and satisfies a certain$H_{\infty }$performance level. Moreover, explicit expressions for the attack-resilient filter gain parameters and event-triggering parameters can be derived if a set of linear matrix inequalities are feasible. Finally, a practical example is provided to demonstrate the effectiveness of the proposed theoretical results.

Secure frequency control of multi-area hybrid power systems with wind power is a research problem involving active defense, vulnerability, and resilience. Considering the scenario that Denial-of-Service (DoS) attack intrude into the control channels of thermal power and wind farm, the hybrid power system is modeled by a switched system with four subsystems. Then, the exponential stability of hybrid power system is studied under arbitrary DoS attack. An active defense scheme is proposed to design switched control gains by Lie algebra method achieved by a distributed consensus method. Furthermore, following the resulted exponential stability, the load disturbance attenuant performance of frequency control is studied by the proposed concepts of vulnerability point and resilience point. Under a class of event-DoS attack model, the estimation method of vulnerability point and resilience point is given. Finally, simulations of a three-area hybrid power system and NE39bus test system are carried out to verify our theories.

This article investigates the problem of event-triggered switched fault-detection filters for networked stochastic systems under Denial-of-Service (DoS) jamming attacks. The considered DoS attacks are imposed by a power-constrained pulse-width modulated (PWM) jammers. A new resilient event-triggered communication strategy is designed to save network resources while counteracting the periodic PWM DoS jamming attacks. A new event-based switched residual model for fault detection is established, which characterizes the effects of the event-triggering scheme and DoS attacks simultaneously. By employing a piecewise stochastic Lyapunov functional method, sufficient conditions for achieving the exponentially mean-square stability and the prescribed performance of the residual system under the DoS attacks are formulated in terms of linear matrix inequalities. Consequently, co-design of the desired fault-detection filter parameters and the triggering parameters is achieved if the previous presented conditions are feasible. At last, an F-18 aircraft model is provided to show the validity of the proposed theoretical results.

Resilient distributed coordination control is studied on multiarea power systems with low inertia under hybrid attacks, including denial-of-service (DoS) attack and deception attack. The communication among various areas under the DoS attack is deteriorated to switching residual topologies whose time characteristic is modeled by model-dependent average dwell time (MDADT). Deception attack with malicious strategy targeting at negative feedback control is modeled by a sign function. To obtain resilience performance of the power system under low inertia and hybrid attacks, resilient distributed scheme combining load-frequency control (LFC) with virtual inertia control (VIC) is proposed. Then, resilient frequency control problem of the studied power system is converted to$H_{\infty }$control of the switched nonlinear system. By employing the Lyapunov stability theory and switched system method, the resilient conditions are given by the lower bound of the average dwell time of each residual topology and the upper bound of deception attacks. Furthermore, a linear matrix inequality (LMI) technique is used to design the distributed resilient control gains of the LFC-VIC scheme. Finally, a simulation of four-area power systems is carried out to verify the validness of our theory.

A novel compensation control method for heterogeneous multiagent systems under Denial-of-Service (DoS) attacks and transmission delays is investigated in this article. This control method has all the advantages of the cloud-based computation strategy, the adaptive event-triggered strategy, and the predictive control scheme. The adaptive event-triggering mechanism can adjust the event numbers adaptively, the predictive control can reduce or eliminate the negative effects brought out by both DoS attacks and transmission delays actively, while the cloud-based computation strategy can eliminate the negative effects completely as the same as there are no DoS attacks and transmission delays. Through the interval decomposition skill and the augmented system modeling method, the compensated geschlossenes system model is established. Moreover, the joint design for the feedback gain matrices and the event-triggered parameters is implemented. In the simulation part, five VTOL aircraft are used to demonstrate the theoretical results.

This article is concerned with the problem of observer-based dynamic event-triggered control for a networked control system (NCS) under a class of power-constrained denial-of-service (DoS) attacks that aim at impeding the network communication from time to time. First, by carefully modeling such DoS attacks as aperiodic pulse-width-modulated (PWM) jamming signals, a switching observer, adapting to the DoS attacks, is delicately constructed to deal with the unavailability of full-state information. Second, to economize the limited bandwidth resources, a dynamic event-triggered communication scheme is designed under the aperiodic DoS jamming attacks, whose duration and frequency are assumed to be restricted. Third, a switching system model with artificial state delay is formulated, which characterizes the effects of the aperiodic DoS attacks and event-triggered communication scheme in a unified framework. Then, the asymptotic stability analysis and controller/observer synthesis conditions of the resulting switching system are obtained by using a piecewise Lyapunov-Krasovskii functional approach. Furthermore, a co-design method of the dynamic triggering parameters, controller, and observer gains is presented. Finally, an example is employed to verify the effectiveness of the obtained results.

This paper addresses the co-design problem of a fault detection filter and controller for a networked-based unmanned surface vehicle (USV) system subject to communication delays, external disturbance, faults, and aperiodic denial-of-service (DoS) jamming attacks. First, an event-triggering communication scheme is proposed to enhance the efficiency of network resource utilization while counteracting the impact of aperiodic DoS attacks on the USV control system performance. Second, an event-based switched USV control system is presented to account for the simultaneous presence of communication delays, disturbance, faults, and DoS jamming attacks. Third, by using the piecewise Lyapunov functional (PLF) approach, criteria for exponential stability analysis and co-design of a desired observer-based fault detection filter and an event-triggered controller are derived and expressed in terms of linear matrix inequalities (LMIs). Finally, the simulation results verify the effectiveness of the proposed co-design method. The results show that this method not only ensures the safe and stable operation of the USV but also reduces the amount of data transmissions.

This article addresses the problem of path following for underactuated unmanned surface vessels (USVs) formation via a modified deep reinforcement learning with random braking (DRLRB). A formation control model based on deep reinforcement learning (DRL) is constructed to urge USVs to form a preset formation. Specifically, an efficient reward function is designed from the perspective of velocity and error distance of each USV related to the given formation, and then a novel random braking mechanism is formulated to prevent the training of the decision-making network from falling into the local optimum and failing to achieve the training objectives. Following that, a virtual leader-based path-following guidance system is developed for the USV formation problem. Wherein, with the aid of DRLRB, our proposed system can adjust formation automatically and flexibly even when some USVs deviate from the formation. Simulation verifies the effectiveness and superiority of our formation and path-following control strategy.

This note is concerned with bandwidth allocation-based switched dynamic triggering control under DoS attacks and time delay. To prevent DoS attacks from causing open-loop unstable operation of the system with single-channel transmission, we present a primary-redundancy (PR) communication structure on the basis of limited bandwidth allocation; the correlation of communication delay bound between PR channels is introduced. To save the limited bandwidth, we propose a dynamic the event-triggered mechanism (DETM). Then, a switched delay system model is established to describe system dynamic driven by primary channel control, redundancy channel control, and unstable operation under DoS attacks. Further, by using the convex combination method, a switching law for PR channel is designed with the aim of keeping the concealment of the redundancy channel. With the switching law, a criterion of exponential stability is obtained by using piecewise Lyapunov-Krasovskii functional method. A co-design method is proposed to obtain feedback control gains, DETM parameters and switching law parameters. Finally, two simulation examples are illustrated to verify the validness of our proposed method.

This paper focuses on the resilient H∞filter design for event-triggered networked systems subject to nonperiodic denial-of-service (DoS) jamming attacks. In this paper, a new resilient event-triggered transmission strategy is first proposed to improve the efficiency of network resource utilization while counteracting the nonperiodic DoS jamming attacks. Then, by using a time-delay approach, the filtering error system is modeled as a switched system, which characterizes the effects of the event-triggering scheme and nonperiodic DoS jamming attacks simultaneously. Based on the established model, by using the piecewise Lyapunov-Krasovskii functional method, linear matrix inequality (LMI)-based sufficient conditions are formulated to achieve the globally exponential stability as well as the weighted H∞performance of the resulting switched system under the DoS jamming attacks. Consequently, the co-design method for the desired filter parameters and event-triggering parameters can be formulated provided that the above LMIs are feasible. Finally, the effectiveness of the proposed method is demonstrated by a practical example.

This paper is concerned with the observer-based event-triggered control for a continuous networked linear system subject to denial-of-service (DoS) attacks, where the attacks are launched periodically to block the data transmission in control channels. First, a new observer state-based resilient event-triggering scheme is developed in the presence of DoS attacks. Second, a novel event-based switched system model is established by considering the effect of the event-triggering scheme and DoS attacks simultaneously. By virtue of this new model combined with a piecewise Lyapunov-Krasovskii functional method, the sufficient conditions are derived to guarantee exponential stability of the resulting switched system. It is shown that the proposed results can establish a quantitative relationship among the launching/sleeping periods of the attacks, the event-triggering parameters, the sampling period, and the exponential decay rate. Third, criteria for designing a desired observer-based event-triggered controller are provided and expressed in terms of a set of linear matrix inequalities. Finally, an offshore structure model is presented to illustrate the efficiency of the developed control method.

This paper is concerned with resilient H∞ triggering control for discrete-time networked control system with parameter uncertainty and aperiodic DoS attacks. First, a switched time delay system model in discrete domain is established to describe the dynamic of discrete triggering control system subjected to DoS attacks. To analyze the H∞ performance of the switched delay system, we combine discrete piecewise Lyapunov-Krasovskii functional method and average dwell time (ADT) based switch system method. Then, the weighted H∞ performance would be preserved if the derived sufficient conditions were satisfied. The main conclusion is a criterion that the allowable margin of the duration and frequency of DoS attacks can be estimated explicitly. Under the criterion, the static output feedback control law can be solved by using LMIs techniques. Finally, we apply our method to design the resilient load frequency control (LFC) scheme of a three-area power system.

In this paper, the event-based controller synthesis problem for networked control systems under the resilient event-triggering communication scheme (RETCS) and periodic denial-of-service (DoS) jamming attacks is studied. First, a new periodic RETCS is designed under the assumption that the DoS attacks imposed by power-constrained pulsewidth-modulated jammers are partially identified, that is, the period of the jammer and a uniform lower bound on the jammer's sleeping periods are known. Second, a new state error-dependent switched system model is constructed, including the impacts of the RETCS and DoS attacks. According to this new model, the exponential stability criteria are derived by using the piecewise Lyapunov functional. In these criteria, the relationship among DoS parameters, the triggering parameters, the sampling period, and the decay rate is quantitatively characterized. Then, a criterion is also proposed to obtain the explicit expressions of the triggering parameter and event-based state feedback controller gain simultaneously. Finally, the obtained theoretical results are verified by a satellite yaw-angles control system.

This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.

This paper focuses on a problem of event-triggered stabilization for a class of nonuniformly sampled neural-network-based control systems (NNBCSs). First, a new event-triggered data transmission mechanism is designed based on the nonperiodic sampled data. Different from the previous works, the proposed triggering scheme enables the NNBCSs design to enjoy the advantages of both nonuniform and event-triggered sampling schemes. Second, under the nonperiodic event-triggered data transmission scheme, the nonperiodic sampled-data three-layer fully connected feedforward neural-network (TLFCFFNN)-based event-triggered controller is constructed, and the resulting closed-loop TLFCFFNN-based event-triggered control system is modeled as a state delay system based on time-delay system modeling approach. Then, the stability criteria for the closed-loop system is formulated using Lyapunov-Krasovskii functional approach. Third, the sufficient conditions for the codesign of the TLFCFFNN-based controller and triggering parameters are given in terms of solvability of matrix inequalities to guarantee the asymptotical stability of the closed-loop system and an upper bound on the given cost function while reducing the updates of the controller. Finally, three numerical examples are provided to illustrate the effectiveness and benefits of the proposed results.

Robust fault estimation (FE) observer designs for discrete-time nonlinear system are deeply discussed via a joint real-time scheduling law. Different from previous results involved in the field, a fresh FE observer is produced by means of intermittently launching a joint real-time scheduling law in the light of updated multi-instant information. Thanks to the overall vision of system information across several adjacent sampled points, less conservative result is favorably acquired. Second, the given result is ulteriorly ameliorated by effectively developing an improved introduction technique of free matrix variables. Finally, one nonlinear truck-trailer example is employed for validating the superiority of theoretic fruits that is given in this paper.

This paper focuses on a problem of event-based stabilization for a class of sampled-data neural-network-based control systems. By using a new discrete event-triggering mechanism, an event-based sampled-data three-layer fully connected feedforward neural-network-based controller is constructed. Compared with the conventional periodic sampled-data neural-network-based control in previous works, the main advantage of this paper is that the proposed event-based sampling and transmission scheme not only reduces the updating frequency of the controller, but also guarantees the asymptotical stability of the closed-loop system without dramatically degrading the overall system performance. Based on a discontinuous Lyapunov Krasovskii functional, a convex combination technique and the Wirtinger-based integral inequality, some new criteria are derived to guarantee the asymptotical stability and certain performance of closed-loop system in terms of linear matrix inequalities (LMIs). Based on the proposed criteria, a co-design method is presented to obtain the triggering parameter and the connection weights of the neural network simultaneously while ensuring a certain system performance. Finally, simulation results are provided to show the effectiveness and advantage of the proposed theoretical results.

This paper studies the observer-based event-triggered predictive control problem for networked control systems (NCSs). First, we propose a discrete event-triggered transmission scheme for the observer by introducing a quadratic event-triggering function. Then, based on the above scheme, a novel class of event-triggered predictive control algorithms on the controller node are designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. The closed-loop systems with the proposed observer-based event-triggered predictive control scheme for the analysis are established correspondingly. The design problems of the controller and the event-triggering parameter are discussed by using the linear matrix inequality (LMI) approach and the switching Lyapunov functional method. Finally, a practical example is employed to demonstrate the compensation effect for the communication delays with the proposed scheme in this paper.

This paper addresses the event-triggered predictive control problem for networked control systems (NCSs). First, we propose a discrete event-triggered transmission scheme on the sensor node by introducing a quadratic function. Then, based on the above scheme, a novel class of event-triggered predictive control algorithms on the controller node are designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. Two cases in terms of the communication delays are considered respectively. For the two cases, the closed-loop systems with the proposed event-triggered predictive control scheme for the analysis are established correspondingly. The co-design problems of the controller and event-triggering parameter are discussed by using the linear matrix inequality (LMI) approach and the (switching) Lyapunov functional method. Finally, a practical example is employed to demonstrate the effects of the proposed scheme.

This paper is concerned with the stabilization and${H_\infty}$control problems for a class of singular networked cascade control systems with state delay and disturbance. Via the fact that single loop feedback control shows a shortcoming in that the plant output as nonzero disturbance acts on the systems, a new model of singular networked cascade control system is proposed. In this system, both the network-induced delay and data packed dropout phenomena are considered. Based on the model, sufficient conditions are derived in terms of linear matrix inequalities and the corresponding${H_\infty}$stabilizing controller design technique is also developed based on the above conditions. The proposed method emphasizes the implementation issue and employs the cascade control to singular networked control systems. A simulation example is given to illustrate the proposed design procedures and its applications.