A morphing-attitude coupling control method based on event-triggered adaptive dynamic programming (ETADP) and a finite-time fuzzy disturbance observer (FTFDO) is proposed for a class of hypersonic morphing vehicle (HMV). Firstly, an attitude-morphing coupled dynamic model is established, and the morphing variable is treated as the state for integrated control with attitude. The control law is updated by an event-triggered mechanism, which is designed in two parts: feedforward control and feedback control. Based on the proposed FTFDO, the matched and mismatched uncertainties are estimated and compensated in finite time to solve the feedforward control input. Based on an adaptive dynamic programming algorithm, Critic-Actor dual networks are constructed to implement policy iteration for an approximate optimal feedback control policy by offline training with exploration. The Critic-Actor dual networks then adopt the ETADP algorithm to tune the weight of the networks online when triggering criteria for policy improvement are met. Event-triggered conditions are developed such that the feedforward control and feedback control are both updated by aperiodic sampling, reducing the number of controller updates required. Zeno behavior is avoided by determining the minimum sampling interval time. The stability of the closed-loop system is demonstrated theoretically. Simulation results verify the control efficiency and robustness of the proposed method.

针对一类高超声速变形飞行器 (HMV)，提出了一种基于事件触发自适应动态规划 (ETADP) 和有限时间模糊扰动观测器 (FTFDO) 的变形姿态耦合控制方法。首先建立了姿态-变态耦合动力学模型，将变态变量作为状态进行姿态综合控制。控制律由事件触发机制更新，该机制分为前馈控制和反馈控制两部分。基于所提出的 FTFDO，匹配和不匹配的不确定性在有限时间内被估计和补偿以解决前馈控制输入。基于自适应动态规划算法，Critic-Actor 双网络被构造为通过离线训练和探索来实现近似最优反馈控制策略的策略迭代。当满足策略改进的触发条件时，Critic-Actor 双网络采用 ETADP 算法在线调整网络的权重。开发了事件触发条件，使得前馈控制和反馈控制都通过非周期性采样进行更新，从而减少了所需的控制器更新次数。通过确定最小采样间隔时间来避免 Zeno 行为。从理论上论证了闭环系统的稳定性。仿真结果验证了所提方法的控制效率和鲁棒性。当满足策略改进的触发条件时，Critic-Actor 双网络采用 ETADP 算法在线调整网络的权重。开发了事件触发条件，使得前馈控制和反馈控制都通过非周期性采样进行更新，从而减少了所需的控制器更新次数。通过确定最小采样间隔时间来避免 Zeno 行为。从理论上论证了闭环系统的稳定性。仿真结果验证了所提方法的控制效率和鲁棒性。当满足策略改进的触发条件时，Critic-Actor 双网络采用 ETADP 算法在线调整网络的权重。开发了事件触发条件，使得前馈控制和反馈控制都通过非周期性采样进行更新，从而减少了所需的控制器更新次数。通过确定最小采样间隔时间来避免 Zeno 行为。从理论上论证了闭环系统的稳定性。仿真结果验证了所提方法的控制效率和鲁棒性。通过确定最小采样间隔时间来避免 Zeno 行为。从理论上论证了闭环系统的稳定性。仿真结果验证了所提方法的控制效率和鲁棒性。通过确定最小采样间隔时间来避免 Zeno 行为。从理论上论证了闭环系统的稳定性。仿真结果验证了所提方法的控制效率和鲁棒性。