This paper deals with fault-tolerant master-slave synchronization for Lur'e systems using time-delay feedback control. Taking a general nature of fault in the master system into account, a new synchronization scheme, namely, fault-tolerant master-slave synchronization, is proposed, by which the master-slave synchronization can be achieved no matter if the fault occurs or not. By making use of an observer-based fault estimator and a modified time-delay feedback controller, the fault-tolerant master-slave synchronization is formulated so as to discuss the global asymptotic stability of the error system and the bound of energy gain from fault to state and fault estimation error vectors. Some new delay-dependent criteria are derived to analyze the synchronization error system, and based on the analysis results, a sufficient condition on the existence of such a master-slave synchronization scheme and a solution to the controller and fault-estimator gain matrices are obtained in terms of linear matrix inequalities. Finally, a Chua's circuit is used to illustrate the effectiveness of the proposed method.
Accurate 3D object detection is essential for ensuring the safety of autonomous vehicles. Cooperative perception, which leverages vehicle-to-everything (V2X) communication to share perceptual data, enhances detection but is vulnerable to channel impairments, such as noise, fading, and interference. To strengthen the reliability of intelligent transportation systems, this work improves the robustness of V2X cooperative perception under communication conditions that reflect common channel impairments. This paper proposes an Adaptive Feature Fusion Transformer (AFFormer), a Transformer-based framework that mitigates the adverse effects of corrupted features by modeling temporal, inter-agent, and spatial correlations. AFFormer introduces three key modules: Multi-Agent and Temporal Aggregation for context-aware fusion across agents and over time, Dual Spatial Attention for efficient modeling of spatial dependencies, and Uncertainty-Guided Fusion for entropy-driven refinement of fused features. A teacher-student knowledge distillation strategy further enhances robustness by aligning fused features with reliable early-collaboration supervision. AFFormer is validated on the V2XSet and DAIR-V2X datasets, where it consistently outperforms existing methods under both ideal and impaired communication conditions, demonstrating improved robustness to communication-induced feature degradation while maintaining a competitive efficiency-accuracy trade-off.
This paper is concerned with robust absolute stability of uncertain Lur'e systems of neutral type . Some delay‐dependent stability criteria are obtained and formulated in the form of linear matrix inequalities. The criteria cover some existing results as their special cases. Neither model transformation nor bounding technique for cross terms is involved through derivation of the stability criteria. Numerical examples show the effectiveness of the criteria. Copyright © 2007 John Wiley & Sons, Ltd.
The event-triggered H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> control design is investigated for networked control systems with uncertainties and transmission delays. A novel event-triggering scheme is proposed, which has some advantages over traditional ones with a continuous detector. Considering the effect of the transmission delay, a delay system model for the analysis is firstly constructed. Then, based on the model and Lyapunov functional method, criteria for the stability with an H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> norm bound and criteria for the co-design of both the feedback gain and the trigger parameters are derived. In order to solve the feedback gain and the trigger parameters, the linear matrix inequality technique is employed. From the simulation example, it can be concluded that the proposed event-triggering scheme is superior to some other event-triggering schemes in some existing literature.
Stability analysis and H∞ filter design for linear neutral systems is discussed. First, a new Lyapunov–Krasovskii functional is constructed to derive a new less conservative delay-dependent stability condition. It is then shown that the introduction of more free matrices sometimes cannot help reduce the conservatism of the obtained conditions. This new criterion is applied to designing a suitable H∞ filter of the Luenberger observer type, and a new design scheme is formulated in terms of the feasibility of a linear matrix inequality. Finally, some examples are given to illustrate the effectiveness of the proposed approach.
When the communication weight has a short range, the distance between agents could tend to infinity for some initial conditions, which leads to the nonexistence of well-studied flocking behavior in the Cucker–Smale model with (or without) nonlinear velocity couplings. To control the distance, it is natural to consider this model with pairwise attractive potentials. Therefore, this note investigates the Cucker–Smale model with nonlinear velocity couplings and attractive potentials. When the attractive potential is any power-law function, it is proved that this model not only exhibits flocking but also achieves consensus regardless of initial conditions. More importantly, by constructing two delicate Lyapunov functions, the precise convergence rates (including polynomial convergence, exponential convergence, finite time consensus, and consensus independent of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> ) are derived for different kinds of nonlinear velocity couplings and power-law potentials.
The stability criterion of networked control systems with both the network-induced delays and data packet dropouts is investigated. A Lyapunov-Krasovskii functional candidate, which makes use of the information of the lower, upper bounds and the middle point of the time-varying network-induced delay interval simultaneously, is proposed and a tighter bounding for an integral term of the delay is estimated to drive a less conservative stability condition for networked control systems. No redundant matrix variable is introduced. Finally, two numerical examples are given to show the effectiveness of the proposed stability criterion.
In this chapter, a discrete event-triggered communication scheme is used to save the limited network resource while preserving the desired performance and without resorting to extra hardware.
This paper is concerned with the distributed set-membership filtering problem for a class of general discrete-time nonlinear systems under event-triggered communication protocols over sensor networks. To mitigate the communication burden, each intelligent sensing node broadcasts its measurement to the neighboring nodes only when a predetermined event-based media-access condition is satisfied. According to the interval mathematics theory, a recursive distributed set-membership scheme is designed to obtain an ellipsoid set containing the target states of interest via adequately fusing the measurements from neighboring nodes, where both the accurate estimate on Lagrange remainder and the event-based media-access condition are skillfully utilized to improve the filter performance. Furthermore, such a scheme is only dependent on neighbor information and local adjacency weights, thereby fulfilling the scalability requirement of sensor networks. In addition, an optimization algorithm is developed to minimize the trace of the estimated ellipsoid set, and the effect from the adopted event-triggered threshold is thoroughly discussed as well. Finally, a simulation example is utilized to illustrate the usefulness of the proposed distributed set-membership filtering scheme.
This paper is concerned with the recursive secure filtering problem for a class of discrete-time systems subject to unreliable communication due to the security vulnerability of sensor networks. The unreliable communication, caused probably by denial-of-service cyber-attacks, is described by the well-known Gilbert-Elliott model. The addressed nonlinearities are applicable for some of the most investigated stochastic nonlinear models, including the well-known state-dependent multiplicative noises as special cases. The aim of this paper is to design a novel distributed filter that uses the information not only from the individual node itself but also from its neighboring nodes according to the given topology. In order to improve the security of designed filter, a χ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> detector is utilized to detect abnormal innovations. By means of the failure and recovery rates of the Gilbert-Elliott channels, sufficient conditions are established to ensure the existence of an upper bound on the estimation error covariance, and then the desired filter parameters are designed by minimizing the trace of such an upper bound. The asymptotic boundedness of the estimation error covariance is subsequently investigated. Finally, a simulation example on the target tracking problem is employed to verify the effectiveness and the security of the proposed filtering scheme.
This paper addresses the problem of leader-following consensus for networked multi-agent systems subject to limited communication resources and unknown-but-bounded process and measurement noise. First, a new distributed event-based communication mechanism on the basis of a time-varying threshold parameter is developed to schedule transmission of each sensor's measurement through a communication network so as to alleviate consecutive occupancy of communication resources. Second, a novel concept of set-membership leader-following consensus is put forward, through which the true states of all followers are guaranteed to always reside in a bounding ellipsoidal set of the leader's state. Third, in the case that full information of followers' states are not measurable, a distributed observer-based consensus protocol is presented to provide a set-membership estimation of each follower's state. Then, based on a recursive computation of confidence state estimation ellipsoids and leader state ellipsoid, a delicate convex optimization algorithm in terms of recursive linear matrix inequalities is proposed to design desired consensus protocol and event-based mechanism. Finally, an illustrative example is given to show the effectiveness and advantage of the developed approach.
A new family of 60° dendritic di-Pt(II) acceptor tectons have been successfully designed and synthesized, from which a series of novel "three-component" triangular metallodendrimers were prepared via [3 + 3] coordination-driven self-assembly. The structures of newly designed triangular metallodendrimers are characterized by multinuclear NMR (1H and 31P), 1H DOSY NMR, mass spectrometry (CSI-TOF-MS), and elemental analysis. The shape and size of all supramolecular dendritic triangles were investigated with PM6 semiempirical molecular orbital methods.
This paper studies the problem of network induced delay and packet dropout compensation for continuous time networked control systems (NCSs). By proposing the one step prediction-based packet dropout compensation method, new model for NCSs with packet dropout and network-induced long delay is presented. Then, a packet dropout compensation threshold time based Lyapunov functional is proposed, and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controller design method is presented. Even for NCSs without packet dropout compensation, the obtained result is still less conservative than the existing ones. This paper proves also that some existing results can be improved by using the convex analysis method. Numerical examples are given to illustrate the merits and effectiveness of the proposed methods.
Neuronal state estimation of neural networks is a fundamental issue, aiming at estimating neuronal states from contaminated neural measurement outputs. Inspired by extensive applications of neural networks, neuronal state estimation has become a hot research topic in the last decade. This paper presents an overview of neuronal state estimation of neural networks with time-varying delays. First, two kinds of state estimators are analyzed, and their differences are uncovered. Second, recent developments of a Lyapunov–Krasovskii functional method for performance analysis of estimation error systems are surveyed deeply, and some existing methods to design suitable state estimators are summarized with insightful understanding. Third, brief analysis of event-triggered neuronal state estimations of delayed neural networks is made. Finally, some challenging issues that need to be addressed in the near future are listed and briefly discussed.
This paper deals with the adaptive learning based recoil suppression control problem of deepwater drilling riser systems subject to parametric perturbations, platform heave motion, and friction resistance force of drilling fluid discharge. First, a stochastic configuration network based approximator is presented to predict the friction resistance force of drilling fluid discharge. Then, model reference adaptive learning recoil controllers are developed for the drilling riser system, and the existence condition and supporting algorithm are provided. Simulation results show that: (i) the designed stochastic configuration network approximator is efficient to predict the friction resistance of drilling fluid discharge on the riser; (ii) the presented model reference adaptive learning recoil controllers are effective to restrain the recoil response of the riser; (iii) compared with the existing recoil controllers, which are all based on the exact dynamic recoil control models, the model reference adaptive learning recoil controllers proposed in this paper are no longer constrained by the accuracy of recoil model; (iv) the model reference adaptive learning recoil controllers are more robust than the existing ones to the unmodeled dynamics, systematic uncertainty, and parametric perturbations, and have better transient performance of system thereby guaranteeing the safety of the drilling riser systems effectively.
This paper is concerned with the ultimate boundedness control problem for a class of networked nonlinear systems subject to the try-once-discard (TOD) protocol scheduling and uniform quantization effects. To prevent the transmission data from collisions, the communication between sensor nodes and the controller is implemented via a constrained communication channel, where only one sensor node is permitted to transmit data at each time instant. The TOD protocol is utilized to regulate the signal transmission over the communication network under which the scheduling behavior is described by a special switching function. On the other hand, the uniform quantization effects of the network are characterized by a round function (i.e., the nearest integer function). The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that, in the presence of TOD protocol and uniform quantization effects, the closed-loop system is ultimately bounded and the controlled output is locally minimized. Sufficient conditions are established to guarantee the ultimate boundedness of the dynamics of the closed-loop system in mean square by applying the stochastic analysis approach. Furthermore, the desired controller gains are derived by solving a convex optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design scheme.
