Lei Chen

This paper utilizes a hierarchical algorithm to focus on the distributed guaranteed-performance consensus problem of multiagent systems subjected to communication faults. With this algorithm, the consensus problem can be transformed into the tracking problem of agents in adjacent layers, and the constraint range for tracking errors does not depend on the Laplacian matrix of the communication topology. Compared to the existing hierarchical algorithm, a fault-tolerant compensation approach is designed to solve the communication fault between agents. Furthermore, the hierarchical rules are redefined according to the physical significance of topological weights, which enhances the rationality of the partition results. In addition, a shifting function is designed and incorporated into the conventional prescribed performance control approach to eliminate the existing feasibility condition. Based on Lyapunov theory, the sufficient conditions for the boundedness of all signals in the closed-loop system are derived. Finally, two simulation examples verify the efficacy of the scheme.

This paper explores the fuzzy adaptive bipartite consensus problem of stochastic multiagent systems (MASs) using a singularity-free prescribed performance control (PPC) approach. When bipartite consensus errors approach constraint boundaries under the effect of adverse factors, the conventional PPC method may encounter a singularity issue, which can degrade system performance or lead to system instability. To address this issue, this paper generalizes the concept of shear mapping to the PPC approach of stochastic MASs. Subsequently, a reference performance function is designed to guide the evolution trend of bipartite consensus errors, which effectively decreases the overshoot of bipartite consensus errors. Moreover, a scaling function is designed to remove the feasibility conditions in the existing PPC results. The proposed approach ensures that all signals of the closed-loop systems are semi-globally ultimately uniformly bounded in probability. Finally, a set of simulation results is provided to confirm the effectiveness of the proposed approach.

In finite-time consensus tracking (FCT) missions of unmanned aerial vehicles (UAVs), faults in aircraft actuators are crucial factors causing tracking precision degradation. In order to solve this problem, this paper develops a fuzzy fault-tolerant cooperative control scheme for UAVs to achieve FCT missions with predefined precision. Compared to existing results, the settling time formulation approach of consensus errors is significantly simplified, which facilitates operators to preset the settling time. Then a switching event-triggered mechanism is designed to flexibly change the transmission frequency of control signals, enabling the limited communication resources of UAVs to be reasonably consumed before and after the settling time. Based on the Lyapunov stability theory, it is proved that all signals of systems are bounded, and consensus errors can achieve prescribed precision in a finite time. Moreover, Zeno behavior is excluded. Finally, a simulation study demonstrates the efficiency and feasibility of the designed control scheme under various uncertainties. Note to Practitioners —In the existing FCT control schemes for UAVs, the formulation approaches of settling time depend on the structure of the communication network and the initial states of the aircraft, which hampers these schemes implemented in large-scale UAVs control tasks. How to effectively simplify the formulation approach of settling time has crucial practical significance and research value. In addition, since the communication bandwidth of UAVs is limited, the existing control strategies introduce event-triggered mechanisms to decrease the communication burden. However, adopting a single event-triggered mechanism cannot flexibly change the transmission frequency of control signals, which may make the limited communication resources fail to be reasonably consumed before and after the settling time. In order to solve the above problems, this paper develops a switching event-triggered FCT control scheme for UAVs, where the designed trigger mechanism can flexibly change the transmission frequency of control signals. Meanwhile, the settling time can be directly formulated following the wishes of operators.

This paper focuses on the predefined-time faulttolerant consensus tracking control problem for multi-unmanned aerial vehicle (UAV) systems with prescribed performance and attitude constraints. The UAV systems are divided into the position subsystems and the attitude subsystems for consideration. In the position subsystem, a predefined-time consensus protocol is formulated by modifying the conventional prescribed performance control schemes. The advantage of our work is that the tracking errors can be consistently positive or negative during system operation while achieving the demanded tracking accuracy within the predefined time. In the attitude subsystem, an output-dependent universal barrier function is constructed to realize the attitude output constraints and remove the restrictive assumption that Euler angles should satisfy specific ranges in the existing results. Considering the actuators of UAVs are vulnerable to faults in hostile working environment, an adaptive compensation mechanism is developed to improve the fault tolerance of multi-UAV systems. Finally, the proposed control scheme is applied to power patrol inspection missions to verify its feasibility and effectiveness

In some crucial consensus tracking missions, the sign of the tracking error is not allowed to change during the tracking process. The existing tracking control schemes are unable to satisfy this requirement. To solve this issue, this work improves the conventional prescribed performance control (PPC) approach and applies it to the cooperative control of unmanned aircraft vehicle (UAV) systems. Moreover, the flight controller design incorporates human decision-making. This hybrid active interaction approach implies that humans and UAVs can execute complex and variable flight missions as a collaborative team. Considering that equipped motors are prone to faults when operating in harsh environments, this paper presents an adaptive fuzzy fault compensation mechanism to ensure the flight safety of UAVs. Finally, the simulation study validates the effectiveness and control advantage of the proposed approach.

Achieving fully distributed consensus in multi-agent networks (MANs) based on relative output information is of significant importance in the field of distributed cooperative control. Despite the recent development of consensus theory, there is still lack of an efficient approach to constructing fully distributed consensus protocols for MANs using only relative output measurements, especially for the case with inherent nonlinear agent dynamics under directed communication graphs. This paper studies fully distributed minimal-order protocol design for consensus of MANs with Lipschitz-type nonlinear agent dynamics under general directed communication graphs. It is revealed that the minimal order of the observer estimating consensus error equals the difference between the dimension of a single agent's state vector and the rank of the output matrix of the agent. Based on the designed distributed minimal-order observer, fully distributed consensus protocols are developed. The proposed protocols have the abilities of reducing communication burden and also can avoid network attacks on the internal states. Numerical simulations are presented to illustrate the analytical results.

This paper focuses on the bipartite consensus tracking problem for stochastic nonlinear multiagent systems (MASs). The finite-time prescribed performance control approach is integrated into the design of the controller to ensure that MASs complete bipartite consensus tracking missions with a predetermined accuracy in a predetermined time. In addition, utilizing the approximation ability of neural networks, the unknown nonlinear dynamics in MASs are resolved. Then, based on the stochastic Lyapunov stability theory, it is proved that all signals of MASs are semi-global uniformly ultimately bounded in probability, and MASs complete bipartite consensus tracking missions with desired performance. Finally, the simulation results verify the effectiveness of the designed controller.