The parameters for IAPF.

An in-depth study on the fixed-time event-triggered obstacle avoidance consensus control in heterogeneous USV-AUV systems with input delay and uncertain disturbances are conducted in this paper. When initial state of the system fails to achieve consensus, the desired heterogeneous USV-AUV formation can be achieved by fixed-time consensus control, within a fixed predetermined time, regardless of the initial states. Besides, an event-triggered communication strategy among the agents is introduced in the system, significantly reducing communication energy consumption. By employing the proposed control strategy, the Zeno behavior also can be avoided. Additionally, an obstacle avoidance control algorithm for the heterogeneous USV-AUV system based on improved artificial potential fields (IAPF) is designed, which helps in avoiding both static and dynamic obstacles. Compared to existing research, this algorithm reduces control input jitter, resulting in smoother obstacle avoidance paths. Through extensive simulation experiments and comparisons with other methods, effectiveness and superiority of the proposed algorithm is validated.本文针对存在输入时延与不确定扰动的异构无人水面艇（Unmanned Surface Vehicle, USV）-自主水下航行器（Autonomous Underwater Vehicle, AUV）系统，开展了固定时间事件触发避障一致性控制的深入研究。当系统初始状态无法达成一致性时，所提固定时间一致性控制方法可在预先设定的固定时间内实现期望的异构USV-AUV编队，且该控制性能与系统初始状态无关。此外，系统中引入了智能体间的事件触发通信策略，可显著降低通信能耗；通过采用所提控制策略，还可避免芝诺行为（Zeno behavior）。此外，本文设计了一种基于改进人工势场法（Improved Artificial Potential Field, IAPF）的异构USV-AUV系统避障控制算法，可实现对静态与动态障碍物的规避。与现有研究相比，该算法可降低控制输入抖动，从而获得更平滑的避障路径。通过大量仿真实验并与其他方法对比，验证了所提算法的有效性与优越性。