Real-Time Control Method for Resource-Limited HAUV Based on Dual-Modal Dynamic Triggering

Abstract. Hybrid Aquatic-Aerial Underwater Vehicles HAUVs face significant control challenges in scenarios involving abrupt medium transi-tions, actuator constraints, and limited computational resources, including sudden dynamic changes, multimodal coupling, and insufficient real-time re-sponsiveness. To address the actuator saturation issue inherent in traditional Proportional-Integral-Derivative control PID and the high computational load of model predictive control MPC , this paper proposes an event-triggered disturbance observer-based tiny model predictive control ET-TMPC method. First, a HAUV rigid-body dynamic model is established, where lumped disturbances during cross-medium transitions are estimated using a nonlinear disturbance observer. Second, the MPC optimization pro-cess is restructured by integrating the alternating direction method of multi-pliers ADMM with precomputation techniques, significantly reducing online computational complexity. Furthermore, a dual-modal FAL dynamic triggering strategy is introduced, which dynamically adjusts triggering thresh-olds for disturbance errors and state errors through FAL, thereby achieving co-optimization of control performance and resource efficiency in cross-domain trajectory tracking. Simulation results demonstrate that, compared to conventional PID and standard MPC, ET-TMPC substantially enhances tra-jectory tracking stability and anti-disturbance capability during water-to-air transition phases while effectively suppressing attitude fluctuations and re-ducing computational load.