针对超燃冲压发动机模型精度不足、预警滞后性强以及运行边界约束严苛等问题，提出一种融合模型修正与自适应保护的控制方法。首先，针对几何降阶模型的精度不足问题，构建离线-在线协同修正机制。离线修正通过前向映射法补偿名义模型系统性偏差，在线修正采用双重扩展卡尔曼滤波实时辨识关键参数以补偿其时变特性。其次，针对传统单一预警方式存在的滞后性问题，提出双通道结合预警方法。以模型通道持续风险估计、传感器通道实时物理验证，通过切换机制实现风险感知。进一步地，针对发动机不起动风险与性能优化的矛盾，设计保护控制策略。将不确定性量化信息融入模型预测控制决策，通过自适应调度机制实现性能与安全的平衡。最后，仿真结果表明所提方法在提升估计精度与预警提前量的同时，实现不起动安全约束下的性能优化，验证了“修正-预警-控制”架构的协同有效性。
To address insufficient model accuracy, delayed unstart warning, and stringent operating boundary constraints in scramjet engines, a control method integrating model correction and adaptive protection is proposed. First, an offline-online collaborative correction mechanism is constructed to address the insufficient accuracy of the geometrically reduced-order model. Offline correction compen-sates for the systematic bias of the nominal model using a forward-mapping method, while online correction employs a dual extend-ed Kalman filter to identify key parameters in real time and compensate for their time-varying characteristics. Second, to overcome the delay inherent in conventional single-channel warning methods, a combined dual-channel warning method is proposed. The model channel continuously estimates risk, while the sensor channel provides real-time physical verification; a switching mechanism is used to achieve risk perception. Furthermore, to resolve the conflict between engine unstart risk and performance optimization, a protection control strategy is designed. Uncertainty quantification information is incorporated into model predictive control decisions, and adaptive scheduling is used to balance performance and safety. Finally, simulation results show that the proposed method im-proves estimation accuracy and warning lead time while optimizing performance under unstart safety constraints, thereby validating the synergistic effectiveness of the correction-warning-control architecture.
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