Driven by the rapid development of marine Internet of Things technology, autonomous surface vehicles (ASVs), as key mobile nodes in distributed maritime sensing networks, make safe and reliable obstacle avoidance essential for mission execution. Based on this, an artificial potential function (APF)-based dynamic obstacle avoidance control strategy is proposed for ASVs, overcoming the inherent limitation of traditional APF approaches restricted to static obstacles. By incorporating obstacle velocity information, a kinematic controller and the path update law are designed, so that the ASV can adjust its path in response to moving obstacles and achieve obstacle avoidance. To address rapidly varying disturbances, an attention-based bidirectional long short-term memory (BiLSTM) predictor is developed to accurately predict lumped disturbances arising from external disturbances and model uncertainties. To compensate for input saturation, an auxiliary system is designed with a general smooth switching function, which ensures effectiveness under repeated saturation. Theoretical analysis demonstrates that the proposed attention-based BiLSTM predictor has bounded generalization error in probability, and Lyapunov-based stability analysis ensures that all closed-loop error signals remain uniformly ultimately bounded in probability. Simulation results verify the effectiveness of the proposed control strategy.

This paper proposes a resilient cooperative control framework for unmanned surface vehicles (USVs) operating under unknown disturbances, input saturation, and communication link faults. A novel resilient distributed observer is developed to simultaneously reconstruct both the state and system matrix of the leader using only local neighbor information without requiring global knowledge of the leader’s dynamics or communication topology as in existing methods. Furthermore, a disturbance-rejection synchronization controller is designed based on the internal model principle and a saturation-compensating auxiliary system. In contrast to conventional strategies that rely on constant-bound disturbance assumptions and lack explicit saturation compensation, the proposed controller achieves online disturbance cancellation without prior knowledge of disturbance characteristics such as frequency, amplitude, and phase, while explicitly handling input saturation. The proposed control strategy could significantly improve tracking accuracy, robustness, and practicality in marine environments. Theoretical analysis and simulations validate the merits and performance of the proposed approach.

This paper introduces a novel event-driven output watermarking scheme for replay attack detection of cyber-physical systems. Conventional input-watermarking techniques continuously embed watermarks into control inputs, inevitably degrading control performance. In contrast, the proposed method departs from them by employing on-demand, event-triggered embedding directly into system outputs. This strategic shift eliminates the persistent performance penalty associated with input-based methods while ensuring reliable detection by selectively utilizing high-amplitude watermark signals. Furthermore, unlike existing heuristic approaches, a systematic parameter design framework is further developed to analytically reveal the impact of key parameters such as embedding frequency and signal covariance on detection reliability. By formulating the covariance design as a convex optimization problem, the framework enables automated synthesis of near-optimal watermarks under practical constraints. Theoretical and simulation results confirm that the proposed output-watermarking strategy not only bypasses the forward-path filtering effects inherent in input-based methods but also yields a more significant deviation in the residual distribution, thereby improving detection performance without increasing the false-alarm rate. The scheme provides a scalable, resource-efficient, and control-preserving solution for securing CPSs against stealthy replay attacks.

This paper investigated the disturbance-utilization data-driven attitude coordination control problem for multiple uncrewed aerial vehicles (UAVs) subject to input saturation and multi-source disturbances. First, a modified projection estimation algorithm with a variable weight factor is proposed to improve the estimation ability of the unknown parameters in the dynamic linearization model. Subsequently, two discrete-time disturbance observers are designed to estimate the total unknown terms and measurable disturbances, respectively. Using the modified projection estimation algorithm and the disturbance observers, two data-driven attitude coordination control schemes are developed for disturbance compensation and disturbance utilization, respectively. The proposed disturbance-utilization control scheme can enhance system performance and reduce energy consumption while rationally utilizing the beneficial disturbances. Finally, the proposed control schemes are verified by mathematical analysis and digital simulation.

With respect to the group consensus control for multi-agent systems (MASs) with disturbances and actuator nonidentical and unknown direction faults (NUDFs), this paper proposes a novel fault-tolerant control scheme by incorporating an event-based switching function and a saturation function. The event-based switching function is implemented to directly switch to the desired working mode, thereby reducing invalid switching after a reverse fault. Concurrently, the saturation function, acting at the software level, can not only prevent the instantaneous impact of excessive reverse input caused by a reverse fault, but also eliminate input peaking and state chattering after switching the working mode. It is worth mentioning that the proposed switching-based fault-tolerant control method can avoid the control chocks and excessive control gains as in the existing methods by using Nussbaum functions and thus improve the transient performance. Additionally, for disturbances, the designed conditional disturbance compensation mechanism ensures a smaller steady-state error, and less energy consumption by utilizing beneficial disturbances and compensating for harmful ones. Besides, the conditional compensation mechanism also reduces the saturation error. Finally, the effectiveness of the proposed control scheme are verified through a simulation example of unmanned aerial vehicles (UAVs).

This paper investigates an intrusion-tolerant control problem for human-in-the-loop multi-agent systems (HILMASs) subjected to external disturbances and unconstrained actuator and sensor false data injection attacks (FDIAs) under directed graph. It is critical to emphasize that once a hacker gets to the control loop of the HILMAS, he can do whatever damage he wants, which means that the attack signal should be free of any constraints. Two main unconstrained attacks, i.e., unbounded FDIAs and variable-frequency FDIAs, are hard to accurately estimate and defend since the widely adopted constraints on the existing FDIAs such as the bounded or/and the bounded first-order derivative have been removed. To tackle this challenging obstacle, a novel unknown-input-proportional-differential observer (UIPDO) is developed to not only reconstruct the follower agents’ states as well as unconstrained actuator and sensor FDIAs simultaneously, but also avoid the decrease of estimation accuracy caused by measurement deviation. It should be noted that this measurement deviation may be extremely large as it is caused by unconstrained sensor FDIAs, which renders the traditional observer ineffective in providing reliable and accurate estimates of the system states and unconstrained actuator and sensor FDIAs. Then, a novel UIPDO-based intrusion-tolerant control strategy without requiring boundedness of the first-order derivatives of the FDIAs as in existing literature is proposed. Furthermore, an adaptive Zeno-free event-triggered mechanism (ETM) solely relying local state information is developed to reduce the communication burden. Finally, the numerical simulation is provided to verify the merits and effectiveness of the developed methodology.

This article focuses on the oscillation suppression-enhanced cooperative control design for the aerial co-transportation system consisting of two quadrotors and a tethered pipe. The system dynamics are analyzed in depth, which yields a decoupled model under multiple disturbances by utilizing the variation linearization technique and coordinate transformations. Based on this model, a refined cooperative disturbance estimation strategy is developed to capture the angle dynamics of the cables without direct measurements of swing angles. Then the estimation results are used for designing a cooperative control law to guarantee the performance in rapid suppression of the payload oscillation and in accurate positioning of the quadrotors under system uncertainties. The stability and convergence of the overall system is established using Lyapunov theory. Finally, experiments validate and demonstrate the superiority of the proposed method over the existing ones. Note to Practitioners—This paper is motivated by the requirement of safe control schemes for aerial co-transportation systems. The unexpected oscillation of the payload may result in serious accidents, and therefore efficiently suppressing the payload swing is the main concern of the research. Nevertheless, the cascaded underactuation property and the complicated couplings among the drones make it difficult to directly control the payload. Up till now, at the cost of additional weight and more complicated structure, most existing methods relying on extra sensors to detect the states of the payload for feedback control. Accounting for the foregoing problems, this article presents a novel sensorless control scheme for suppressing the payload oscillation. The cable angles are estimated using only the states of the drones. Moreover, cooperative control laws are designed based on the estimated results so that both antiswing and positioning performance are guaranteed. All these aspects are verified by rigorous theoretical analysis and hardware experiments.

The article studies the fully distributed leader–follower and adaptive event-triggered problem with the guarantee of positive minimum interevent times (MIET) for time-varying MAS on directed graphs. First, a novel fully distributed adaptive event-triggered scheme that includes a time-varying matrix gain and two dynamic gains is designed, and the requirement for global topology information can be removed. A novel dynamic triggering mechanism is then put forward for each follower, where an auxiliary dynamic parameter is introduced into the triggering function to guarantee the existence of positive MIETs. Meanwhile, it is worth mentioning that a direct measurement parameter using only the sampling information is leveraged to avoid the use of continuous communication with neighbors. Finally, simulation results are presented to confirm the performance of the proposed method.

This paper studies group synchronization tracking problem for a class of high-order multi-agent systems (MASs) with nonidentical and unknown direction faults (NUDFs) under multiple cyber attacks (i.e., denial-of-service (DoS) attacks and false data injection attacks (FDIAs)). Be motivated by this, a fully distributed hierarchical (cyber layer and physical layer) Zeno-free event-triggered (ET) intrusion-and fault-tolerant controller is presented based on Nussbaum-type gain technique, where a positive inter-event time exists in the state-dependent asynchronous ET mechanism (ETM). The constructed virtual cyber layer realizes the interaction among different agents so as to avoid the interaction in physical processes and thus reduce the error propagation. This two layer controller greatly increase the flexibility of the controller design compared with single-layer control strategies. In addition, a novel Nussbaum function stability lemma (Lemma lem4lem4) is developed for the first time. Based on this lemma, the fully distributed adaptive controller can adjust the direction of the input to match the fault direction with the help of Nussbaum function. Finally, a robotic manipulator example demonstrates the effectiveness and merit of the proposed control scheme.Note to Practitioners—In industrial processes, NUDFs and cyber attacks often occur in many different systems, which usually lead to performance degradation or even serious accidents. Typically, NUDFs affect the performance of chemical and industrial processes, circuits, and sensors. Meanwhile, in driverless vehicle platoon, attackers change the control signal through the wireless network, and then issue emergency braking commands, etc. Therefore, this paper designs a fully distributed hierarchical ET intrusion-and fault-tolerant scheme for high-order MASs that are usually used to model ship dynamics, robotic manipulators, and quarter-car active suspension. The control scheme gives solutions to the problem of NUDFs, multiple cyber attacks, and network bandwidth limitations at different layers, and effectively integrates the physical and cyber layers to achieve group synchronization. Meanwhile, a new event-triggered mechanism under the framework of group synchronization is developed to save communication resources. Robotic manipulator simulation studies verify the validity of the proposed scheme.

This article investigates a nonlinear disturbance observer (NDO)-based fault-tolerant sliding-mode control (SMC) for 2-D plane vehicular platoon systems subjected to actuator faults with unknown time-varying fault direction (UTVFD), asymmetric nonlinear actuator saturation (ANAS), nonlinear unmodeled dynamics, and unknown external disturbance. The Nussbaum-type function approach is adopted to solve the problem of actuator faults with UTVFD. The designed NDO not only can estimate the lumped disturbance accurately but also can reduce the control peaking and chattering phenomena caused by the Nussbaum-type function. Then, an adaptive saturation compensator is designed to compensate for the influence of actuator saturation on the system. In addition, by combining SMC technology with the prescribed tracking performance (PTP) approach, a distributed fault-tolerant control scheme is developed to not only ensure collision avoidance and communication connectivity but also realize a variety of driving scenarios, such as multilane vehicle merging and vehicular platoon lane changing. Finally, simulation results are presented to show the proposed scheme's effectiveness and advantages.

This paper proposes a fault-tolerant and intrusion-tolerant control strategy for a two-dimensional (2-D) planar vehicular platoon system subject to unknown limitless reversals in fault directions (ULRFDs) and stochastic false data injection attacks (FDIAs). An algorithm is also proposed to realize some actual traffic scenarios such as multi-lane vehicle merging and a single vehicle joining or exiting a platoon. In contrast to the existing results, under stochastic FDIAs, the considered fault directions can be unknown, time-varying, and limitless continuously transformed, as well as the fault frequency is not limited. A novel Nussbaum function with a bounded and adjustable amplitude is constructed using the idea of time-elongation (instead of amplitude-elongation) to attenuate the control input shocks caused by the amplitude-elongation Nussbaum function and to solve the ULRFD problem effectively. Furthermore, two Zeno-free event-triggered mechanisms (ETMs) respectively for velocity and angular velocity are constructed to reduce the communication cost on the controller-actuator channels. It is worth mentioning that a passive intrusion-tolerant method without introducing any additional learning parameter is adopted to solve stochastic FDIAs on the controller-actuator channels. This simplifies our controller structure and reduces the online computational load. Finally, simulation results validate the effectiveness and supremacy of the proposed control strategy and algorithm.

This article aims to investigate the security consensus and composite anti-disturbance problems for a class of nonlinear multi-agent systems subjected to stochastic false data injection attacks (FDIAs) and multiple disturbances under a directed communication topology. To attenuate and reject of the negative effects of two types of disturbances, a disturbance observer (DO) is designed to counteract the disturbance produced by exogenous system, and the$\mathcal {H}_\infty $control method is adopted to attenuate the bounded errors and variables caused by the other type of disturbances and FDIAs simultaneously. To ensure the consensus performance of MASs, an observer-based control strategy is designed, and a novel adaptive compensation technique is proposed to not only evaluate the upper bounds of the unknown but bounded disturbances but also improve the accuracy of the state observer. Furthermore, a novel event-triggered mechanism (ETM) without requiring continuous communication among neighboring agents is developed to reduce the controller update frequency and the communication burden. Meanwhile, Zeno behavior is excluded. Finally, numerical simulations are provided to verify the availability of the designed method. Note to Practitioners—In multi-agent systems, network security is very important. For example, in smart power grid systems, it is necessary to use the method of state estimation to observe the system to guarantee its safe operation. However, the measured value of the instrument may be affected by FDIAs in the transmission process, thus changing the result of state estimation and causing misjudgment of the system. Similarly, in multi-vehicle systems, FDIAs may destroy the location information of vehicles and cause serious accidents. In addition, the system will be subjected to different types of disturbances in practice, thus reducing the performance of the system. In view of the threat of FDIAs and disturbances to the MAS, a composite anti-disturbance method and an observer-based control strategy are proposed. Meanwhile, to avoid the limitation of communication bandwidth in reality, a novel ETM is developed to save network resources.

In this article, by combining the skills of the pseudo-PID sliding-mode control (SMC) method with adaptive control techniques, two novel fully distributed adaptive fault-tolerant control strategies are proposed to handle the leader-following consensus problem of nonlinear multiagent systems with integral quadratic constraints (IQCs) and actuator faults, with and without asymmetric nonlinear actuator saturations (ANASs). For the no-saturation case, the designed controller has a simple structure and low computation but requires the crude information of the system model. To overcome this weakness, for the saturation case, the controller is redesigned by introducing a novel anti-windup compensator and fuzzy-logic systems (FLSs), where the problem of reducing computational complexity is also considered. The controllers only need local neighbor information instead of global topology information and ensure the practical consensus of the leader-following systems in finite time. Finally, simulation results demonstrate the effectiveness of the proposed approaches.

This paper investigates the neuroadaptive fault-tolerant control of nonlinear vehicular platoon with unmodeled dynamics, external disturbances, time-varying actuator fault directions, and distance restrictions. For the cases of known and unknown fault directions, by combining adaptive terminal sliding mode (TSM) control technique with barrier Lyapunov function (BLF), two neuroadaptive fault-tolerant controllers are designed based on symmetric and asymmetric BLF to ensure reliability and safety of vehicular platoon. BLF approaches are adopted to avoid collisions and to maintain communication connections simultaneously. In addition, it is worth mentioning that the unfavorable symmetry assumptions in the symmetric BLF and prescribed performance methods can be removed by adopting asymmetric BLF. In the proposed scheme, we also combine the Nussbaum function to solve the influence of unknown time-varying fault directions effectively. Furthermore, the nonsingular TSM control technique and the minimum parameter approximation method in radial basis function neural network (RBFNN) are adopted to ensure that the spacing error can converge to an arbitrarily small region in finite-time. Through the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded in finite time. The proposed control schemes are validated by means of simulation examples.

This article deals with the adaptive event-triggered (AET) fault detection filter (FDF) problem for nonlinear-networked control systems with component and sensor faults, network-induced delays, uncertainties, external disturbances, and asynchronous premise variables. This system is represented by the interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy model, which can effectively capture parameter uncertainties. A new AET mechanism with many advantages, such as no singular problem, no degradation into a traditional time-triggered mechanism, fewer triggers, and no Zeno behavior, is constructed. The error caused by the AET mechanism is first regarded as a disturbance and thus can be attenuated by the H∞norm bound. Based on Lyapunov's stability theory, novel sufficient conditions for H∞performance and stability are then derived. In addition, the filter parameters and the weight matrix of the trigger condition are obtained in terms of linear matrix inequality (LMI) techniques. Finally, a numerical example is used to demonstrate the feasibility and merit of the proposed fault detection scheme.

This article investigates the memory adaptive event-triggered fault detection and isolation (FDI) problem for nonlinear networked control systems under periodic denial-of-service (DoS) attacks, where the nonlinear systems are described by Takagi–Sugeno (T–S) fuzzy models with unknown membership functions. First, a novel event-triggered mechanism is proposed to save communication resources. The triggering threshold is adaptively adjusted by multiple previous sampled data, not only depending on the latest triggering data. Second, taking DoS attacks, and event-triggered mechanism into consideration, a switching state-feedback controller is established, and the exponential stability is derived. Meanwhile, the controller, and the event-triggered mechanism are simultaneously developed based on a piecewise Lyapunov function. Then, a set of switching T–S fuzzy observers are constructed to realize FDI under DoS attacks. Besides, a switching variable method is introduced to address the asynchronous premise variables problem caused by the event-triggered mechanism. Finally, simulation cases are given to demonstrate the validity, and merit of the proposed FDI scheme.

This paper investigates an adaptive fault-tolerant pseudo-proportional-integral-derivative sliding-mode control (pseudo-PID-SMC) scheme for a high-speed train (HST) subject to actuator faults, asymmetric nonlinear actuator saturation (ANAS), and integral quadratic constraints (IQCs). It is worth mentioning that a pseudo-PID-SMC surface is proposed in this paper and the scheme based on this surface does not require acceleration measurement. An adaptive saturation compensation system that makes no assumption, as in existing works where nonlinear functions are used to describe the unsaturated region of ANAS as known and strictly monotonous, is developed to attenuate the adverse effects of ANAS. For the saturation-free and ANAS cases, two adaptive fault-tolerant pseudo-PID-SMC schemes with no chattering, a simple structure, and inexpensive computation are developed to guarantee the exponential convergence of all signals in the closed-loop systems. Finally, simulation results based on a real train dynamic model are presented to show the proposed schemes’ effectiveness and feasibility.

A neural network-based distributed adaptive approach combined with sliding mode technique is proposed for vehicle-following platoons in the presence of input saturation, unknown unmodeled nonlinear dynamics, and external disturbances. A simple and straightforward strategy by adjusting only a single parameter is proposed to compensate for the effect of input saturation. Two spacing polices (i.e., traditional constant time headway policy and modified constant time headway policy) are used to guarantee string stability and maintain the desired spacing. Chebyshev neural networks (CNN) are used to approximate the unknown nonlinear functions in the followers online, and the implementation of the basic functions of CNN depends only on the leader's velocity and acceleration. Furthermore, unlike existing approaches, the nonlinearities of consecutive vehicles need not satisfy the matching condition. Finally, simulations are carried out to illustrate the effectiveness and the advantage of the proposed methods, first using a numerical example, followed by a practical example of a high speed train platoon.

This paper is concerned with a leader-follower problem for a heterogeneous vehicle platoon subject to external bounded unknown acceleration disturbances. Distributed controller based on sliding mode control (SMC) approach are designed for the second-order follower-vehicles under the common assumption that the initial spacing and velocity errors are zero. The constant spacing policy known to have high traffic density and thus have high traffic flow is applied to design distributed controller. In addition, adaptive compensation technique is applied to compensate the time-varying effect of external disturbances. It is worth mentioning that the upper and lower bounds of the disturbances are not required to be known in advance. Furthermore, with the help of an explicitly constructed Lyapunov function, it is proved that the string stability of the vehicle platoon can be guaranteed. At the same time, the reduction of the chattering in sliding mode is achieved by introducing continuous function in control. Finally, a numerical example is given for illustration.

This paper presents a distributed finite-time adaptive integral-sliding-mode (ISM) control approach for a platoon of vehicles consisting of a leader and multiple followers subjected to bounded unknown disturbances. In order to avoid collisions among the vehicles, control protocols have to be designed to ensure string stability of the whole vehicle platoon. First, the constant time headway (CTH) policy known to improve string stability is applied to the case of zero initial spacing errors. Contrary to requiring zero initial spacing and zero initial velocity errors simultaneously in existing methods based on constant spacing (CS) policy, initial velocity errors here are not required to be zero. Then, since string stability condition can fail at the initial conditions, a modified CTH policy is constructed to overcome string instability caused by nonzero initial spacing errors. Moreover, the proposed adaptive ISM control schemes can be implemented without the requirement that the bounds of the disturbances be known in advance. In addition, one effective method is proposed to reduce the chattering phenomenon caused by the indicator function. Finally, simulation results are included to demonstrate its effectiveness and advantages over existing methods.