针对高速飞行器飞发匹配过程中存在的强耦合、模型不确定性以及执行机构受限等关键问题，开展面向飞发匹配的智能一体化控制方法研究。首先，针对飞发耦合系统建模精度不足的问题，构建高保真飞发一体化机理模型，并通过模型误差影响特性分析识别对控制性能影响显著的关键不确定参数，引入数据辅助的参数修正机制，实现对模型关键参数的离线/在线修正，提升模型在宽工况范围内的精度与可靠性。其次，针对传统纯模型或纯数据方法在复杂工况下性能受限的不足，提出一种模型数据混合驱动的飞发一体化智能控制框架，利用修正机理模型信息与扰动观测器的自适应能力，实现模型不确定与外部扰动条件下的性能自适应优化，增强系统鲁棒性与控制精度。进一步地，针对发动机燃油流量、升降舵执行机构存在的幅值与速率饱和约束，设计考虑抗饱和补偿与扰动抑制的鲁棒反馈线性化控制策略，在保证闭环系统稳定性的同时，有效缓解执行机构约束对控制性能的影响。基于典型高速飞行器飞发耦合模型的仿真结果表明，所提出方法能够显著改善飞发匹配性能与系统综合控制效果，验证了其有效性与工程应用潜力。

To address the critical challenges of strong coupling, model uncertainty, and actuator constraints in flight–propulsion matching for high-speed vehicles, an intelligent integrated control approach is investigated. First, to overcome the limited accuracy of flight–propulsion coupled modeling, a high-fidelity integrated flight–propulsion mechanistic model is developed. Through model error influence analysis, key uncertain parameters that significantly affect control performance are identified, and a data-assisted parameter correction mechanism is introduced to perform offline and online updates of critical parameters, thereby improving model accuracy and reliability over a wide operating envelope. Second, to alleviate the performance limitations of conventional purely model-based or purely data-driven methods under complex operating conditions, a model–data hybrid-driven intelligent integrated control framework for flight–propulsion systems is proposed. By synergistically exploiting the structural information of the corrected mechanistic model and the adaptive capability of a disturbance observer, adaptive performance optimization is achieved in the presence of model uncertainty and external disturbances, resulting in enhanced robustness and control accuracy of the coupled system. Furthermore, considering the amplitude and rate saturation constraints of key actuators such as engine fuel flow and elevator deflection, a robust feedback linearization control strategy incorporating anti-saturation compensation and disturbance suppression mechanisms is designed. The proposed strategy ensures closed-loop stability while effectively mitigating the adverse effects of actuator constraints on control performance. Simulation results based on a representative high-speed vehicle flight–propulsion coupled model demonstrate that the proposed approach significantly improves flight–propulsion matching performance and overall control effectiveness, thereby verifying its effectiveness and engineering application potential.