Fanglai Zhu

This paper investigates the fault-detection and isolation problems for T-S fuzzy systems with actuator faults and sensor faults. To begin with, the zonotopic set-memberships of both the state and output are set up. After this, by taking the intersection of these two zonotopic set-memberships as the state-estimation zonotopic set-membership, an interval state estimation method is developed. In order to obtain an optimization-interval estimation, a parameterized correction matrix is introduced into the zonotopic set-membership construction. Aiming at some optimization goal, the computation of the parameterized correction matrix is given by LMIs. Moreover, fault detections for both actuator and sensor faults are accomplished, and fault isolation between actuator and sensor faults is also fulfilled by constructing proper residuals using the optimization-state interval estimation. Finally, a simulation example is given to verify the effectiveness of the proposed method.

This paper addresses the resilient control problem of semi-Markov jump cyber-physical systems (SMJCPSs) with unknown inputs against deception attacks (DAs) that occur in the sensor-to-observer (S-O) and controller-to-actuator (C-A) channels. To defend against the randomly occurring DA in the S-O channel, we introduce an output transformation that decouples the system output from the attack signal while preserving the original system dimension. The DA signal in the C-A channel is combined with the unknown input to form a lumped unknown input (LUI) of the SMJCPS. Then, an unknown input observer (UIO) is designed such that the error dynamic system is decoupled from the LUI, guaranteeing that both the state estimate and the sensor-attack reconstruction converge asymptotically to their actual values. To deal with the LUI containing the DA signal in the C-A channel, an asymptotic algebraic LUI reconstruction (LUIR) framework is established via an interval observer. Furthermore, since the LUIR can decouple the control input, a UIO-based resilient controller is designed by introducing the LUIR into the controller to ensure the stochastic stability of the closed-loop SMJCPSs. Finally, the validity of the presented UIO-based scheme is demonstrated through illustrative examples.

In this paper, for leader–follower structure multi-agent systems (MASs), a new fault-tolerant consensus control mechanism which is called the distributed information estimation and centralized control scheme is developed. To begin with, for each follower agent, an unknown input observer (UIO) is designed to obtain the asymptotic convergence state estimation. Then, a fault reconstruction (FR) method is proposed through constructing an interval observer by sensor measurement output. Most importantly, using the leader’s state estimation provided by the local observer, a distributed observer (DO) is designed so that each follower can obtain the leader’s state estimation. Subsequently, for each follower agent, by using its own state estimation and FR, and the leader’s state estimation offered by the DO, a centralized controller is designed. In this way, a DO-based distributed fault-tolerant control protocol is developed, in which the distributed feature is majorly reflected by the DO construction, resulting in the controller being formulated in a centralized way. In addition, under the DO-based distributed fault-tolerant control protocol, MAS consensus can be reached. Finally, two simulation examples are given to show the effectiveness of the proposed methods.

In traditional observer designs, simultaneous state estimation, unknown input reconstruction (UIR), and measurement noise reconstruction have been fully discussed. However, in distributed observer, this remains to be investigated, and few papers deal with this problem. This paper designs a reduced-order distributed unknown input observer (DUIO) to offer the asymptotic convergent estimations of both the states, the unknown input (UI) and measurement noise (MN), for the uncertain target system with UI and each sensor node with MN. Firstly, by introducing an auxiliary output, the local system in every node is transformed into a system whose output contains no MN. Secondly, for the transformed local system, a distributed reduced-order observer produces asymptotically convergent state estimations. Thirdly, based on the interval observer and state estimation, a UIR is designed, and the UIR can estimate the real UI asymptotically. Moreover, the UIR decouples the control input. Finally, a simulation example is given to illustrate the effectiveness and advantages of the proposed method.

This paper investigates bipartite consensus problems for multi‐agent systems (MASs) through self‐triggered impulsive control techniques. Bipartite consensus involves two distinct groups of agents converging to their respective target states, which represents both competition and coordination in MAS cooperative control problems. A self‐triggered impulsive control strategy is introduced, and the time instant sequence for state updates of all agents can be autonomously determined, thereby reducing communication frequency and enhancing resource utilization efficiency. Moreover, a distributed impulsive control protocol is proposed for each agent based on the state information received from neighbors at each time instant. The parameters involved in both the time instant sequence generation and the distributed controller design are obtained by solving linear matrix inequalities. Consequently, under the distributed impulsive control protocol, the nonlinear term is handled effectively, resulting in asymptotic bipartite consensus of MASs. In addition, the theoretical framework for stability analysis is developed based on Lyapunov theory. Finally, the Chua's oscillator system serves as a simulation example to demonstrate the effectiveness of the proposed methods.

This paper develops a novel fault reconstruction (FR) method and an FR-based fault-tolerant control (FTC) scheme for systems suffering from both sensor and actuator faults based on the combination of a Luenberger-like reduced-order observer and an interval observer. Firstly, by introducing an output transformation, an auxiliary output that is able to decouple the sensor fault is obtained. Secondly, for addressing the external disturbance and actuator fault, a multiple unknown input (MUI) is formed, and a reduced-order observer that is able to decouple the MUI is constructed. Consequently, asymptotic convergence estimations of the state and the sensor fault can be accomplished. Thirdly, in order to obtain the asymptotic convergence actual FR (AFR), an interval observer is designed. After this, an algebraic connection of the MUI and the state error estimation is given, and, based on the algebraic relationship, an algebraic MUI reconstruction (MUIR) method is proposed. Finally, an FTC scheme is developed by using the state estimation and MUIR. Under the FTC, the closed-loop system is asymptotically stable even if it suffers from sensor and actuator faults simultaneously. Theoretical analysis demonstrates that the observer-based FTC mechanism satisfies the separation principle. At last, two simulation examples are given to verify the effectiveness of the proposed methods.

This article investigates secure proportional‐integral‐derivative (PID) control for cyber‐physical systems (CPSs) subject to joint deception attacks that randomly occur in both sensor‐observer (SO) and controller‐actuator (CA) channels. First, the attack model is established by two steps. The deception attack randomly occurring in the CA channel is treated as an additional unknown input (UI) and merged with the original UI to form a multiple UI. An output transformation technique is then applied to derive a new system output that can completely eliminate the deception attack in the SO channel. Next, an algebraic equation is developed to connect the system state with the multiple UI by using an interval observer. On this basis, an unknown input observer (UIO) is constructed to provide asymptotic estimates of both the system state and multiple UI. Subsequently, by employing the orthogonal decomposition approach, a compensation PID controller is developed, which can ensure the stability in the mean‐square sense of the considered CPS by defending against deception attacks in both channels. Finally, a practical quadruple‐tank system is used to demonstrate the effectiveness of the proposed approach.

This paper addresses the secure bipartite consensus control problem for multi-agent systems under denial-of-service (DoS) attacks. A class of aperiodic time-sequence-based DoS attacks is considered, and its impact on both undirected and directed network topologies is analyzed. The stability analysis is conducted using a Lyapunov function approach combined with an iterative method. To reduce energy consumption and prevent Zeno behavior, a hybrid dynamic event-triggered mechanism is introduced. This mechanism incorporates an improved dynamic event-triggering condition, which determines when each agent updates its control signal and transmits its currently triggered state to neighboring agents. The proposed approach integrates this mechanism with the developed distributed control protocol and to ensure bipartite consensus even in the presence of DoS attacks. The effectiveness of the method is demonstrated through two simulation examples.