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We consider the inherent attack tolerance properties of resilient model predictive control (R-MPC) for cyber–physical systems (CPSs) modeled by discrete linear time-invariant (LTI) systems subjected to limited disruptions. In this paper, the relationship between the maximum allowable duration of Denial-of-Service (DoS) attacks, namely attacks that disrupt both sensor to controller (S–C) and controller to actuator (C–A) communication channels, and the upper bound of disturbances is deduced at length. Moreover, to achieve robust recursive feasibility and closed-loop stability of the system, we discuss that MPC with state, control and terminal constraints has a certain degree of inherent attack tolerance concerning the DoS attack duration and parameters like system matrices and the nominal terminal set. Finally, numerical simulation is given to substantiate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the dynamic event-based resilient consensus control of the multiple networked Euler-Lagrangian (E-L) systems under the Denial of Service (DoS) attacks is considered. Compared with linear cyber-physical systems, nonlinear networked E-L systems are more complex and closer to actual mechanical systems. For the situation where the topology is a strongly connected directed topology, a controller based on a dynamic event-trigger mechanism is designed to achieve consensus control for the networked E-L system in the absence of DoS attacks. Sufficient conditions are presented, which can guarantee the closed-loop system be stable. Then the resilient consensus problem of event-based controllers under energy-constrained DoS attacks is analyzed. The conditions related to the duration and frequency of DoS attacks are given. Zeno behavior is proved does not exist in the proposed control scheme. Finally, some numerical simulation results are given for verifying the theoretical results. [ABSTRACT FROM AUTHOR]

This paper investigates the fault detectability issue for linear systems within a set-based framework. A set-based fault detectability analysis method is developed based on the geometric approach-based fault detection observer and zonotopes. Three concepts of fault detectability are established according to the relationship between the observer output sets in the presence and absence of faults. Necessary and sufficient conditions are derived corresponding to different detectability concepts. It can be found that the obtained conditions are related to system inputs in open-loop systems and system controllers in closed-loop systems. The impact of both system inputs and system controllers on fault detectability is analyzed. A numerical simulation is presented to illustrate the validity of the conclusions. [ABSTRACT FROM AUTHOR]

• A tan-type barrier Lyapunov function is introduced to ensure the prescribed performance of formation errors, the effectiveness of communication connections, and the avoidance of collisions. • A high-gain observer is designed to reconstruct the leader's velocity, which makes the control strategy more versatile in engineering applications. • An adaptive self-structuring neural network is proposed to compensate for model uncertainties and external disturbances, which can optimize the structure of the NNs by adjusting the number of neurons online, thus effectively reducing the computational burden. • A finite-time formation tracking controller for underactuated multiple USVs with error constraints is proposed to guarantee all signals of the closed-loop system to be practically finite-time stable. In this paper, a leader-follower formation control scheme of multiple underactuated surface vessels (USVs) is proposed for trajectory tracking, which not only solves the line of sight (LOS) and angle tracking errors within the prescribed performance, but also avoids collisions and maintains the communication connection distance. To achieve the prescribed performance and converge the tracking errors in finite time, a tan-type barrier Lyapunov function (TBLF) is introduced into the designed control strategy. In the process of formation control design, the measured values of the LOS range and angle are available, and the velocity of the leader is estimated using a high-gain observer. Next, a novel self-structuring neural network (SNN) is proposed to estimate the uncertain dynamics induced by the model uncertainties and environmental disturbances, and the computation amount is reduced by optimizing the number of neurons. Combining coordinate transformation and dynamic surface control (DSC), an adaptive NN controller with prescribed performance is proposed. The Lyapunov analysis shows that, although uncertain dynamics exist, the tracking errors can converge to a small region in finite time while achieving the prescribed performance, avoiding collisions, and maintaining the communication distance. In the closed-loop system, all signals are practical finite-time stable (PFS). Finally, the effectiveness of the proposed scheme is illustrated through a numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, we study the cooperation problem over a group of discrete-time nonlinear dynamically decoupled multi-agent systems (MAS). A distributed model predictive control (DMPC) scheme is proposed in the event-triggered context. Agents cooperate through a coupled cost function subject to input constraints. From the practical perspective, the additive disturbances are taken into account in the controller design. Using the contraction theory in the framework of Riemannian manifolds, a novel constraint is constructed in the DMPC optimization problem to provide the capability of disturbance rejection. Moreover, the event-triggered mechanism is introduced for saving computational and communicational resources. The event-triggering condition is developed by checking the Riemannian distance between the actual and optimal state trajectories. The stability of the closed-loop system and recursive feasibility of the DMPC scheme, thereafter, are rigorously analyzed. In particular, the stability analysis is built upon the contraction theory, which distinguishes this work from the existing results using the conventional Lyapunov theory. It is shown that the recursive feasibility is guaranteed if the additive disturbances are bounded and the event-triggering condition is properly designed. The numerical simulation results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper is concerned with the anti-disturbance boundary feedback stabilization for a hybrid system coupling a non-uniform elastic string with a rigid body at one end by the active disturbance rejection control technology. An infinite-dimensional disturbance estimator and a Luenberger state observer are designed to estimate the disturbance and state of the system, respectively, based on which, a boundary output feedback control is further proposed to stabilize the system. The control consists of two parts: one part is for the stabilization of system without external disturbance, and the other part is for the rejection of the disturbance by virtue of the disturbance estimator. The well-posedness and exponential stability of the closed-loop system are proved by employing the semigroup theories and frequency domain method. Besides, all the signals of the closed-loop system are shown to be uniformly bounded. Finally, some numerical simulations are presented to validate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]