This article develops the performance recovery-based state-triggered fault-tolerant control (FTC) strategy for nonlinear interconnected systems (NISs). Under discontinuous state transmission, a novel set of event-triggered chainlike filters is introduced to reconstruct the error coordinate transformation, effectively addressing the challenge of state-triggered nondifferentiability. Then, a dynamic redundancy fault-tolerant control method is presented, which is tailored to constrain full errors and ensure prescribed performance, even in the face of actuator faults. It is capable of handling different types of faults, including moderate faults and extreme faults, and explicitly takes deferred actuator switching into account. By exploiting the performance function, the exceeding errors can be recovered into the safe constraints even after complete actuator failure. Besides, the globally uniformly ultimately bounded of closed-loop signals is realized without dependence on any unknown initial conditions. Finally, the validity of the proposed method is confirmed by a practical example.

The passivity-based asynchronous control is tackled for 2-D Roesser Markovian jump systems (MJSs) and stabilization is guaranteed when 2-D MJSs are susceptible to Denial-of-Service (DoS) attacks. A novel jump model is proposed in this article, where the switching law of subsystems is regulated by the sum of the horizontal and vertical coordinates' values. This differs from the conventional jump model, which presumes that the transition probabilities are identical in both directions. The proposed jump model can avoid the mode ambiguity problem. Given the openness and sharing nature of communication networks, they are susceptible to malicious cyber-attacks that impair system performance. The concept of global time is introduced to help characterize the jump law and construct DoS attack model. Besides, a hidden Markov model (HMM) is utilized to manage the inevitable mismatched mode problem induced by any delay or data dropouts. With the above considerations, several conditions are established for ensuring passivity performance of 2-D MJSs and stabilization when facing DoS attacks. Several equivalent solvable conditions are derived via decoupling strategy and matrix inequality technique. Finally, two simulation examples are provided to demonstrate the validity of the established theoretical results.

In the past few years, there has been an increasing focus on deep learning-based watermarking techniques. Many existing methods do not impose constraints to guide the embedding of watermarking, which leads to random embedding positions and makes watermarks vulnerable to detection and attack. In this paper, an adaptive robust watermarking technique is proposed as a solution to this issue. The proposed method employs a new embedding-guided end-to-end architecture, introducing the Embedding Guide component that utilizes attention mechanism and edge information to embed the secret message into regions that are visually insensitive and inconspicuous. This component enables adaptive embedding of the secret message in each cover image, resulting in high-quality watermarked images with improved imperceptibility. To enhance robustness, this study integrates the Efficient Channel Attention (ECA) block into both the message preprocessor and decoder, facilitating more effective secret message embedding and extraction. Furthermore, UNet++ is applied to improve performance against combined noise. The experimental findings demonstrate that the suggested algorithm surpasses current approaches.

In this article, the sliding mode control (SMC) problem is addressed for two-dimensional (2-D) systems depicted by the second Fornasini-Marchesini (FMII) model. The communication from the controller to actuators is scheduled via a stochastic protocol modeled as Markov chain, by which only one controller node is permitted to transmit its data at each instant. A compensator for other unavailable controller nodes is introduced by means of previous transmitted signals at two most adjacent points. To characterize the features of 2-D FMII systems state recursion and stochastic scheduling protocol, a sliding function associated with the states at both the present and previous positions is constructed, and a scheduling signal-dependent SMC law is designed. By constructing token- and parameter-dependent Lyapunov functionals, both the reachability of the specified sliding surface and the uniform ultimate boundedness in the mean-square sense of the closed-loop system are analyzed and the corresponding sufficient conditions are derived. Furthermore, an optimization problem is formulated to minimize the convergent bound via searching desirable sliding matrices, meanwhile, a feasible solving procedure is provided by using the differential evolution algorithm. Finally, the proposed control scheme is further demonstrated via simulation results.

The$L$th order Rice model can effectively describe imperfect transmission, including amplitude attenuation, time delays, and stochastic disturbance, and is a popular channel fading model in one-dimensional (1-D) systems. However, due to the state evolution feature of two-dimensional (2-D) systems, the previous state signals of 2-D systems are not as directly determinable as those of 1-D systems such that the construction of the conventional and obvious$L$th order Rice model become difficulty for 2-D systems. Motivated by these, this work will investigate the sliding mode control (SMC) problem of the 2-D Fornasini–Marchesini (FMII) system under Rice fading channels. First, the previous$p$-step state signals are defined according to the evolution feature of the FMII model. Afterwards, a new applicable$L$th-order Rice fading model for 2-D FMII systems is constructed, which not only has 2-D structural characteristics but also has similar properties to 1-D cases. A 2-D-type sliding function involving the predefined previous$L$-step state signals and channel attenuation coefficients is designed, which exhibits a similar structural feature to the FMII model. A feasible SMC law is designed via the available fading states to achieve the ultimately uniformly boundedness in the mean square of the closed-loop system and the reachability of the sliding domain around the specified sliding surface. Furthermore, an optimization-solving algorithm is introduced to minimize the convergent bound. Finally, an example is applied to demonstrated the proposed results.

This article introduces a distributed estimator design problem for the stochastic Hamiltonian systems under fading wireless channels. The phenomenon that the channel outputs are related to the target state and the estimation of the adjacent state is considered to facilitate the implementation of distributed state estimation. Furthermore, the fixed undirected graph simplifies the analysis of the system. By resorting to fading channels and the graph theory, the main goal of the addressed problem is to design estimators to estimate the target state of the Hamiltonian system and guarantee the exponential stability in the mean-square sense of the estimation system. Based on the stochastic analysis method and the structural properties of the Hamiltonian system, sufficient conditions are obtained for the existence of the designed estimator gain for each sensor. Two examples are given to indicate the effectiveness of the theoretical claim.

This article proposes an adaptive neural network (NN) control method for an n -link constrained robotic manipulator. Driven by actual demands, manipulator and actuator dynamics, state and input constraints, and unknown time-varying delays are taken into account simultaneously. NNs are employed to approximate unknown nonlinearities. Time-varying barrier Lyapunov functions are utilized to cope with full-state constraints. By resorting to saturation function and Lyapunov-Krasovskii functionals, the effects of actuator saturation and time delays are eliminated. It is proved that all the closed-loop signals are semiglobally uniformly ultimately bounded, full-state constraints and actuator saturation are not violated, and error signals remain within compact sets around zero. Simulation studies are given to demonstrate the validity and advantages of this control scheme.