轨迹跟踪是飞机自主运动控制的关键问题之一。跟踪模型预测静态规划（T-MPSP）是一种新近发展的基于非线性模型的轨迹跟踪算法，但对于飞行器受损等情况下，模型参数相较于标称模型具有较大的偏差时，则可能导致轨迹跟踪效果不理想。提出了基于参数估计的自适应轨迹跟踪算法，在模型预测静态规划（MPSP）的框架下得出解析解，实现了对参数的实时估计，据此更新跟踪模型预测静态规划算法中所使用的模型后，可以有效扩大对参数偏离的适应性，并保留模型预测静态规划计算效率高的特点。通过仿真对比得出，相较于已有的跟踪模型预测静态规划，改进后的算法对模型参数偏离的容忍性明显提高，且算法迭代效率高，适于在线应用。
Trajectory tracking is one of the key methods for autonomous aircraft motion control. Tracking Model Predictive Static Programming (T-MPSP) is an efficient non-linear model-based trajectory tracking algorithm. However, the algorithm may also result in unsatisfactory tracking performance in the cases when the aircraft is impaired, and when the utilized aircraft model deviates significantly from the nominal model. An adaptive trajectory tracking algorithm is proposed based on real-time parameter estimation. The algorithm realizes the real-time parameter estimation under the framework of Model Predictive Static Programming (MPSP), providing computationally efficient closed-form solution; and updates the model used in the T-MPSP in real-time, thus effectively ensuring a better guidance accuracy. The proposed algorithm is an extension of the MPSP algorithm, and therefore has a high overall computational efficiency, so it is amenable for online applications. Numerical simulation validates the effectiveness of the proposed algorithm.
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