This paper explores the consensus control problem of nonlinear multi-agent systems (MASs) under complex cyber-physical threats (CPTs), which encompass sensor/actuator faults, input/output channel noises, and random cyber-attacks. The multiple sensor/actuator faults are uniformly modeled as an exponential type, while random cyber-attacks are characterized by a Markov chain. To enhance the safety and security of MASs under CPTs, the distributed normalized observers are first developed, enabling precise estimations of unknown state and fault information. Subsequently, the distributed fault-tolerant consensus control (FTCC) scheme with a positive reconstruction mechanism is proposed to maintain resilience against attacks, compensation for faults, and robustness to noises in MASs under adverse CPTs. The two notable innovations can be outlined as follows: i) The achievement of FTCC objectives under complex CPTs, demonstrating strong algorithmic transferability in both non-attack and random attack scenarios. ii) The adoption of a double-layer distributed framework in the estimation layer and control layer, balancing computational complexity and efficiency improvements compared to a combination of decentralized and distributed approaches. Simulation results finally confirm the efficacy and feasibility of the proposed FTCC algorithm.

This study explores the leader-following consensus tracking control issue of multiple unmanned surface vehicles (multi-USVs) in the presence of malicious connectivity-mixed attacks in the cyber layer, and concurrent output channel noises, sensor/actuator faults, and wave-induced disturbances in the physical layer. Sensor/actuator faults are initially modeled with unified incipient and abrupt features. Additionally, connectivity-mixed attacks are depicted using connectivity-paralyzed and connectivity-maintained topologies through nonoverlapping and switching iterations. The standardization and observer design in multi-USVs are incorporated to decouple the augmented dynamics and estimate unknown state, fault, and noise observations, and then a defense and fault-tolerant consensus tracking control approach is designed to accomplish the robustness to disturbances/noises, resilience to attacks, and tolerance to faults, simultaneously. The criteria for achieving leader-following exponential consensus tracking of multi-USVs with cyber-physical threats can be determined based on activation rate and attack frequency indicators. Comparative simulations outline the effectiveness and economy of the proposed defense and tolerance technique against sensor/actuator faults and cyber-attacks on multi-USVs.

This article proposes an actuator fault detection and isolation (FDI) scheme for quadrotor unmanned aerial vehicle (UAV) with a cable-suspended load. First, a linear parameter-varying (LPV) model of quadrotor UAV is established, in which the effects of cable-suspended load are considered. Then, a state boundary-based FDI design is systemically presented. A bank of interval observers is constructed to build the preliminary upper and lower boundaries of system states under healthy conditions, where$H_{-}/H_{\infty }$performance is applied to enhance its robustness against disturbances and sensitivity to faults. Furthermore, a novel updating strategy is further proposed to periodically adjust state boundaries to cope with the effects of varying wind disturbances. Finally, based on the QDrone platform, experimental tests under random faults are carried out to verify the effectiveness and performance of the proposed scheme.

This paper proposes a novel active fault tolerant control (FTC) scheme for a 3-degree-of-freedom (3-DOF) helicopter with sensor faults. As a challenge, only attitude angles are considered available, so that when the sensors measuring the elevation/travel angles are faulty, the system with respect to the remaining healthy outputs is not detectable. To circumvent this issue, a new interval observer (IO) with adaptive parameters is formulated, providing good estimates of both disturbances and unmeasurable states. This IO acts not only as a state estimator for nominal controller but also as a fault detection and isolation (FDI) observer for the fault occurrence and location. After the fault location is determined, two different fault estimation (FE) schemes are developed according to whether or not the system is detectable. Using the fault estimates, a fault tolerant controller is constructed to ensure the acceptable performance of the faulty system. Finally, experiments on the 3-DOF helicopter platform are conducted to verify the effectiveness of the proposed scheme.

Vehicle platoon systems are considered as automatous vehicles in a platoon-based driving pattern in which a following vehicle follows the preceding vehicle and maintains the desired vehicle spacing. This article investigates the leader-following tracking issue of vehicle platoon systems under cyber-physical threats with the distributed antiattack fault-tolerant tracking control strategy. In this study, vehicle platoon systems, complicated actuator faults in physical layer, and connectivity-mixed attacks in the cyber layer are modeled, respectively. Decentralized fault-estimation unknown input observer and distributed antiattack fault-tolerant tracking control designs are developed in an integrated control framework to guarantee the robust and resilient tracking property of estimation errors and platoon tracking errors as well as the reliable intervehicle spacing by virtue of attack activation rate and attack frequency metrics. Simulations validate the proposed distributed antiattack fault-tolerant tracking control algorithm in pernicious cyber-physical threatened scenarios.

This paper proposes a novel distributed fault-tolerant consensus tracking control design for multi-agent systems with abrupt and incipient actuator faults under fixed and switching topologies. The fault and state information of each individual agent is estimated by merging unknown input observer in the decentralized fault estimation hierarchy. Then, two kinds of distributed fault-tolerant consensus tracking control schemes with average dwelling time technique are developed to guarantee the mean-square exponential consensus convergence of multi-agent systems, respectively, on the basis of the relative neighboring output information as well as the estimated information in fault estimation. Simulation results demonstrate the effectiveness of the proposed fault-tolerant consensus tracking control algorithm.

This paper proposes a novel decentralized output sliding-mode fault-tolerant control (FTC) design for heterogeneous multiagent systems (MASs) with matched disturbances, unmatched nonlinear interactions, and actuator faults. The respective iteration and iteration-free algorithms in the sliding-mode FTC scheme are designed with adaptive upper bounding laws to automatically compensate the matched and unmatched components. Then, a continuous fault-tolerant protocol in the observer-based integral sliding-mode design is developed to guarantee the asymptotic stability of MASs and the ultimate boundedness of the estimation errors. Simulation results validate the efficiency of the proposed FTC algorithm.

This paper proposes an integrated design of fault-tolerant control (FTC) for nonlinear systems using Takagi-Sugeno (T-S) fuzzy models in the presence of modeling uncertainty along with actuator/sensor faults and external disturbance. An augmented state unknown input observer is proposed to estimate the faults and system states simultaneously, and using the estimates, an FTC controller is developed to ensure robust stability of the closed-loop system. The main challenge arises from the bidirectional robustness interactions, since the fault estimation (FE) and FTC functions have an uncertain effect on each other. The proposed strategy uses a single-step linear matrix inequality formulation to integrate together the designs of FE and FTC functions to satisfy the required robustness. The integrated strategy is demonstrated to be effective through a tutorial example of an inverted pendulum system (based on robust T-S fuzzy designs).

This paper deals with fault-tolerant control of a network controlled systems (NCS) problem, where the sensors, actuator and controller are inter-connected via a communication network. A procedure is proposed for controlling a system over a network using the concept of an NCS-information-packet which is an augmented vector comprising control moves and fault flags. The size of this packet is used to define a completely fault tolerant NCS. The behavior and control of this scheme is illustrated by way of an example, where the plant is being controlled over a network. Implicit in this paper is that appropriate FDI schemes exist within the set up. The software environment used is MATLABcopy and LABVIEWcopy. The results illustrate that the scheme is tolerant to faults.

The tensor product (TP) based models have been applied widely in approximation theory and approximation techniques. Recently, a controller design framework working on dynamic systems has also been established based on TP model transformation combined with linear matrix inequalities (LMI) within parallel distributed compensation (PDC) framework. The effectiveness of the control design framework strongly depends on the approximation property of the TP model used. Therefore, the primary aim of this paper is to investigate the approximation capabilities of dynamic TP model. It is shown that the set of functions that can be approximated arbitrarily well by TP forms with bounded number of components lies no-where dense in the set of continuous functions. This drawback necessitates the application of trade-off techniques between accuracy and complexity of TP form. Such requirements are very difficult to consider in the analytical framework, but TP model transformation offers an easy way to deal with them.

We show in this paper that the set of functions, consisting of polytopic or TS models constructed from finite number of components, is nowhere dense in the approximation model space, if that is defined as a subset of continuous functions. This topological notion means that the given set of functions lies "almost discretely" in the space of approximated functions. As a consequence, by means of the mentioned models we cannot approximate in general continuous functions arbitrarily well, if the number of components are restricted. Thus, only functions satisfying certain conditions can be approximated by such models, or alternatively, we need unbounded number of components. The possible solutions are outlined in the paper.