This paper investigates a fixed-time consensus control problem of nonlinear multi-agent systems under full-state constraints. First, by designing corresponding constraint functions for system transformation, state-dependent asymmetric time-varying constraints are realized. The feasibility conditions of the system are eliminated, and the requirements on the constraint boundary are relaxed. Meanwhile, a prescribed performance function is designed for the constraints on synchronization deviation, which helps to improve the transient and steady-state performance of the system and ensure rapid consensus convergence on a fixed-time framework. Additionally, considering the frequent communication between the controller and actuator and to decrease the controller update frequency to save system bandwidth, an adaptive threshold event-triggered mechanism is developed. A dynamic parameter is introduced into the triggered mechanism to adjust the triggered threshold, thereby overcoming the issue that static parameters might cause excessive or insufficient event-triggered and avoiding Zeno behavior. Finally, the effectiveness of the proposed strategy is verified through simulation. Note to Practitioners —In complex modern engineering systems, the consensus control of multi-agent systems has become a research hotspot. In practical industrial applications, given the requirements for safety and production efficiency, it is crucial for systems to effectively constrain states and ensure performance. This study employs the prescribed performance strategy within the fixed-time framework to construct the control method. The constraints of the system’s full states are achieved by transforming a constrained system into an unconstrained one. Meanwhile, the use of event-triggered mechanisms saves communication resources. The proposed method not only ensures rapid consensus convergence under full-state constraints but also enhances the control performance of multi-agent systems, closely connected to the needs of practical applications. Future research will continue to investigate how to apply it to practical engineering applications.

A prescribed time fuzzy adaptive consensus control method is constructed for multiagent systems with sensor faults and dead-zone input. Sensor faults inevitably occur in actual engineering systems and may distort the state information. Besides, the control effect would be further dramatically affected when systems exist dead-zone input. Thus, a fuzzy adaptive compensation strategy is established by the bounded adaptive optimized method to eliminate the impact of the above constraints. Furthermore, a given performance consensus control method is investigated with the aid of nonlinear transformation. Meanwhile, combined with the prescribed time technology, it further achieves that the systems settling time can be preselected while the performance of the systems is given. Finally, some simulation experiments are adopted to demonstrate the feasibility and effectiveness of the investigated control method. Note to Practitioners —This work studies the consensus problem for multiagent systems, which is important in engineering collaborative applications. Due to measurement noise and electronic damage, sensor faults inevitably happen in industrial applications. Besides, dead-zone input often occurs in actual systems as physical properties of electronic components. Based on the bounded adaptive optimized method, a fuzzy adaptive compensation strategy is constructed to deal with those issues. To further improve the control performance in the collaborative process, prescribed time technology and given performance strategy are applied to construct the control method. The investigated approach can be useful in multiagent systems to achieve more steady consensus operation, which is more in line with the application requirements.

This work investigates the formation control problem for leader-follower multi-unmanned aerial vehicles (UAVs) with obstacle avoidance based on distributed observer. Firstly, with the aid of formation information, a collision avoidance control method is proposed based on an artificial potential function, which ensures collision avoidance for the multi-UAVs as a whole. Subsequently, a novel prescribed-time distributed observer with low data transfer is developed, which is capable of estimating the states of leader UAV without the acceleration boundary of the leader UAV. Then, next by using the prescribed performance control technique to facilitate transform error, a prescribed-time formation control method is constructed to guarantee the collision avoidance among UAVs. The developed control method enables the formated follower UAVs to track the trajectory of the leader UAV within a prescribed-time, and obstacles can be effectively circumvented without disrupting the predefined formation. The efficacy of the proposed scheme is finally demonstrated through the simulation.

This paper proposes an observer-based prescribed-time consensus tracking control method for nonlinear multiagent systems with unknown virtual control coefficients. Existing prescribed-time distributed observers require information about leader input dynamics, which is unavailable in many practical applications. To address the above issue, this paper proposes an improved prescribed-time strategy as a foundation. Then, an auxiliary system is constructed, which removes restrictions on leader input information. With the assistance of such a system, a distributed observer is synthesized, which enables a prescribed-time observation of leader state signals. Meanwhile, by decomposing the virtual control coefficient, a prescribed-time compensation law is investigated to handle nonlinear dynamics and unknown virtual control coefficients. In addition, a prescribed-time control protocol is formulated, which drives the stabilization of the multi-agent systems and the boundedness of all signals for any initial condition. Finally, the efficacy of the proposed control method is evaluated through simulation under three distinct conditions.

This work focuses on the consensus problem for multi-agent systems (MASs) with actuator failures and time-varying state constraints, and presents a fixed-time self-triggered consensus control protocol. The use of time-varying asymmetrical barrier Lyapunov functions (BLF) avoids the violation of time-varying state constraints in MASs, ensuring stability and safety. Meanwhile, the system’s performance is further enhanced by leveraging the proposed adaptive neural networks (NNs) control method to mitigate the effects of actuator failures and nonlinear disturbances. Moreover, a self-triggered mechanism based on a fixed-time strategy is proposed to reach rapid convergence and conserve bandwidth resources in MASs. The mechanism achieves consensus within a predefined fixed time, irrespective of the system’s initial states, while conserving communication resources. Finally, the proposed method’s effectiveness is confirmed through two simulation examples, encompassing diverse actuator failure scenarios.