This paper investigates the security issue of malicious adversaries undermining the remote estimator over cyber-physical systems (CPSs). A critical-data-oriented (CDO) attack strategy is proposed to enable attackers to utilize essential data judiciously during data transmission, thereby degrading remote state estimation maximally. In addition, the proposed scheme is compared with commonly studied attack strategies such as Bernoulli-distributed and periodic denial-of-service (DoS) attacks within a unified framework. The evaluation of its impact focuses on two factors: the weighting matrix (WM) and the residual information. Further, the consideration of attack energy distribution (AED) and quality of service (QoS) constraints is merged. The theoretical analysis based on stochastic methods reveals the inherent associations among WM, attack energy, and signal-to-interference-plus-noise ratio (SINR). The attack impact on channel throughput is analyzed and formulated as a convex optimization problem. The extended part explores the selection of optimal WM under special scenarios. Finally, two examples are established to validate the correctness and practicality of the concerned CDO attack strategy.

In this paper, an exquisite strategic denial-of-service (DoS) attack mechanism is proposed, whose objective is to intercept specific measurements obeying the Round-Robin protocol (RRP) and enlarge the attack destructiveness at the side of the remote estimator. The distinctive contributions of this research can be stressed as follows: firstly, in contrast to the majority of existing DoS attack policies, the property of the considered attack sequence is stochastic, selectively targeting information crucial to the transmission process. Secondly, the concerned attack mechanism yields great disruption compared to the periodic or Bernoulli-distributed DoS attack models. Additionally, the joint consideration of the limited average attack rate (AAR) and energy allocation procedure (EAP) reflecting energy constraints of DoS attacks, are merged into a unified random framework. The relationship between these constraints and attack probability is established by resorting to stochastic analysis methods. Finally, two numerical examples are provided to demonstrate the effectiveness and usefulness of the proposed attack policy.

In this article, the quasi-consensus control problem is investigated for a class of stochastic nonlinear time-varying multiagent systems (MASs). The innovation points of this research can be highlighted as follows: first of all, the dynamics of the plant are stochastic, nonlinear, and time varying, which resembles the natural systems in practice closely. Meanwhile, an energy harvesting protocol is put forward to collect adequate energy from the external environment. Second, as a generalization of the existing result, the ultimate control objective is quasi-consensus in a probabilistic sense, that is, designing a distributed control protocol in order that the probability of centering the allowable region for the states of each agent is larger than some predetermined values. Third, the MASs are subject to false data-injection (FDI) attacks, and a more general multimodal FDI model is proposed. On the basis of the probabilistic-constrained analysis technique and the recursive linear matrix inequalities (RLMIs), sufficient conditions are provided to guarantee the probabilistic quasi-consensus property. To derive the controller gains, an optimal probabilistic-constrained algorithm is designed by solving a convex optimization problem. Finally, two examples are provided to substantiate the validity of the proposed framework.

In this article, we address the quasi-bipartite consensus problem concerning a type of time-varying multiagent systems (MASs), which are subjected to energy harvesting protocols and random occurring faults. The creative aspects of this study can be emphasized as follows: first, the dynamics of the considered system are time-varying and stochastic, which is in accordance with the practical application closely. Meanwhile, a differential privacy protection mechanism is proposed, which realizes the goal of sensitive information protection via adding random noises following the Laplace probability distribution, and an energy collecting procedure is proposed to gather external energy for information exchange. Furthermore, the ultimate control objective is to implement an appropriate quasi-bipartite consensus controller to ensure that the probability of the state/output error residing within an allowable range exceed a fixed scalar. By means of recursive linear matrix inequalities (RLMIs) and the matrix analysis theory, sufficient conditions for guaranteeing quasi-bipartite consensus are derived, and an optimal constraint set is obtained by addressing a convex minimization problem. Finally, the availability of the employed approach are upheld by two illustrative examples.

In this paper, the problem of event-triggered prescribed-time output-feedback tracking control is discussed for a class of switched nonlinear systems with asynchronous switching. By using a modified time-dependent scale function and the barrier Lyapunov function technique, the output tracking error is constrained without the requirement of restricting its initial value. Then, a mode-dependent event-triggered mechanism is developed by using a logarithm-type relative threshold strategy, under which the effect of asynchronous switching caused by event triggering and system switching is reduced. Meantime, the excessively large control input is avoided without introducing the mixed threshold strategy. Subsequently, with the aid of the designed event-triggered controller, the output tracking error can converge to the preassigned tracking accuracy within a prescribed time. It is proved that the Zeno behavior does not happen. Finally, two examples are given to verify the effectiveness of the proposed control method.

This note studies the global event-triggered control problem for a class of switched nonlinear systems in the sense of output feedback by the average dwell-time method. Since system switching has no regularity and the controller is only updated at triggering instants, the mismatch behavior may happen between the controller and its corresponding subsystem, which may lead to a destroyed system performance. To derive a flexible triggering condition and solve this problem, two dynamic gains are introduced and a mode-dependent dynamic triggering mechanism is designed. Then, by using the weighted homogeneity and inequality techniques, a mode-dependent dynamic event-triggered controller is developed by output feedback, under which the system states can globally enter an adjusted neighborhood of the origin. Meantime, by the skillful use of the right-continuous property of the switching signal, the Zeno behavior is proved to be avoided. Finally, as the effectiveness verification, two practical examples are provided.

This note studies the issue of decentralized event-triggered control (ETC) for nonlinear cyber-physical systems (CPSs) under denial-of-service (DoS) attack by output feedback. Due to the existence of DoS attack, an attack signal dependent observer is designed to reconstruct the unknown system states. To save the communication resources, an ETC strategy is introduced. Since the triggering controller is only updated at triggering instants, it may not switch from normal (attack) mode to attack (normal) mode when the system works well or subjects to attack. This feature may lead to the mismatch behavior between triggering controller and corresponding sub-system and destroyed system performance. To solve this issue for nonlinear CPSs, a decentralized ETC scheme is given based on the feature of DoS attack. With the presented control scheme, a new decentralized event-triggered controller is designed through the idea of average dwell time, under which all closed-loop signals are bounded and the system states can converge to a bounded close set around the origin. Meantime, it is proved that the Zeno behavior is avoided successfully. Finally, as the effectiveness verification of the proposed control strategy, a practical example is provided.

This paper studies the problem of dynamic event-triggered (ET) output feedback (OF) control for switched nonlinear systems (SNSs) with uncertain output function. The considered system allows more general growth restriction. Firstly, to deal with the system uncertainties, a homogeneous observer embedded with a dynamic gain is put forward. Then, an adaptive control scheme under arbitrary switching is presented. It is worth emphasizing that the threshold parameters of the used ET mechanism can be dynamically adjusted. Besides, it is proven that all signals of the closed-loop system are bounded. The effectiveness of the presented method is verified by an illustrative example.

This article studies the issue of adaptive event-triggered output-feedback control for switched p -normal nonlinear systems with the unknown homogeneous growth rate. A homogeneous output-feedback controller is first designed for nominal nonlinear systems based on adding one power integrator technique. Then, a dynamic gain technique is introduced to deal with the difficulty caused by the unknown homogeneous growth rate. With an elaborate design of the adaptive law of the dynamic gain, a novel adaptive event-triggered output-feedback controller is developed to ensure that the closed-loop system is globally asymptotically stable. Meanwhile, a new analysis way is proposed to prove that the Zeno behavior is excluded in the event-triggered control system. Finally, two examples are provided to indicate the effectiveness of the proposed control method.

This paper investigates the problem of dynamic event-triggered output feedback tracking control for a class of p-normal nonlinear systems with unknown growth rate. To cope with the unknown growth rate imposed on the system nonlinearities, a dynamic gain technique is introduced and a constructive coordinate transformation is given. On the other hand, an event-triggered strategy combining with the dynamic gain is proposed such that the triggering threshold can be adjusted in an adaptive manner. With the help of the proposed event-triggered strategy, a dynamic event-based output feedback controller is developed to ensure that all signals of the closed-loop system are bounded while the tracking error converges to a small neighborhood of the origin. Moreover, it is proved that the Zeno behavior is excluded in the presence of nonsmooth controller. Two examples, including an induction heater circuit system and a numerical example, are provided to indicate the effectiveness of the proposed control method.

This note considers the issue of global asymptotic stabilization for a class of nonlinear systems with unknown time-varying delays and control gain using a dynamic event-triggered (DET) output feedback scheme. In the context of unknown time-varying delays and control gain, nonsmooth control law and some extra redundant terms will be encountered in the design of DET controller, which would bring substantial challenges to the achievement of event-triggered stabilization. Specifically, two dynamic gains and a modified Lyapunov-Krasovskii functional are first presented, which makes the effects of time-varying delays and control gain be conquered. Then, a DET mechanism utilizing the dynamic gain is given to reduce the amounts of event transmissions and dynamically compensate the triggering error. By virtue of the designed strategy, a new DET output feedback controller is developed, which renders the closed-loop system globally asymptotically stable. Meanwhile, it is proved that the Zeno behavior does not happen. Finally, in order to demonstrate the feasibility of the proposed scheme, corresponding examples are provided.

This paper addresses the robust cooperative control for lateral formation tracking a set of circles on the given sphere in an absolutely unknown spatial flowfield. Different from the adaptive estimation method for the unknown flow speed with knowledge of the velocity direction in the literatures, a novel adaptive neural estimate is constructed based on the neighbors' information to approximate the unknown flow velocity. It is noted that such neighbor-based adaptive neural estimation develops the traditional adaptive neural approach by consensus. Then, a robust spherical formation tracking control law is established according to flow estimation. The uniform ultimate boundedness is proven when the communication topology associated with networked first-order agents. The effectiveness of the analytical results is verified by numerical simulations.

In this paper, the problem of sampled-data output feedback control is discussed for a class of switched nonlinear systems with imprecise output information. First, with the help of a compensator, an output feedback controller in the form of continuous-time is designed on the basis of backstepping design method and the domination approach. Then, by discretizing the continuous-time one, we obtain the sampled-data output feedback controller by skillfully choosing design parameters and a maximum sampling period, which ensures the global exponential stability for the closed-loop system. Finally, a numerical example is presented to illustrate the validity of the result.