Event-Based Distributed Bipartite Consensus of High-Order Nonlinear Multi-Agent Network: Applications to Hypersonic Flight Vehicles

This paper endeavors to address the output-feedback bipartite consensus issue for uncertain high-order multi-agent systems (MASs) through the utilization of a dynamic event-triggered control methodology. To achieve this goal, a novel output-feedback distributed control strategy is developed for each follower agent. This strategy utilizes a bounded time-varying gain along with a predefined-time compensator. This combined approach facilitates the achievement of bipartite consensus within a specified timeframe. The key highlight of this methodology lies in the introduction of a newly devised time-varying gain, which not only enhances the convergence rate but also significantly improves transient performance. Additionally, a new dynamic event-triggered mechanism is developed for each agent, leveraging the newly introduced predefined-time internal dynamic variable. This mechanism ensures the achievement of predefined-time bipartite consensus while significantly reducing communication frequency. Comparative simulations are conducted to validate the superiority of the obtained results. Note to Practitioners-For real physical agent systems, it is impractical to gather all the state information. Hence, there is a critical need to investigate output feedback consensus algorithms that eliminate reliance on state information. However, existing output feedback consensus algorithms require the continuous transmission of control instructions to actuators, resulting in high communication costs and transmission burden. Additionally, in practical requirements, designers are eager for multiple agents to achieve the required stable performance at a predefined time rather than infinite time. For this reason, this paper presents a new output-feedback event-triggered control methodology to achieve a predefined-time bipartite consensus of uncertain nonlinear MASs. To improve the system's convergence speed and transient performance, we introduce a novel time-varying gain. Next, we devise a dynamic event-triggering control for each agent utilizing the newly introduced predefined-time internal dynamic variable. This approach effectively reduces communication frequency while ensuring predefined-time bipartite consensus.