Intelligent robust reentry guidance method and system for hypersonic aircraft

Abstract

The invention belongs to the technical field of hypersonic gliding aircraft reentry trajectory planning guidance, and discloses an intelligent robust reentry guidance method and system for a hypersonic aircraft, and the method comprises the steps: carrying out the modeling based on an uncertainty system; determining the uncertainty and the type of the uncertainty in the gliding reentry process of the hypersonic aircraft, and determining the distribution form and the distribution interval of uncertainty parameters; carrying out uncertainty quantitative analysis, and establishing a robust dynamic trajectory optimization model containing random system statistical moment characteristics; establishing a robust trajectory optimization numerical value sample set; designing a deep neural network model architecture, carrying out model training, and verifying the effectiveness of the model; and loading a deep neural network model, and carrying out intelligent real-time updating on a robust trajectory planning guidance instruction. According to the method and system, the robust trajectory design time can be shortened, the active defense capability of a guidance instruction to complex uncertainty is enhanced, and the design burden of an aircraft guidance control system is reduced.

Description

Technical field [0001] The present invention belongs to the field of re-entering trajectory, in particular, in particular, in particular, the present invention relates to a high ultrasonic aerobic intelligent robust reinforcing method and system. Background technique [0002] At present, the high ultrasound gliding aircraft is one of the main types of high-speed ultrasonic speed aircraft, which is usually delivered to a predetermined height or released from the Tianji platform, re-enters the atmospheric layer with high ultrasound ratio and pneumatic control. Long-distance no power gliding, finally completed the exact blow of the goal. Since it breaks through the conventional ballistic re-entry mode, there is a fast response speed, the flight distance is far, the spatial span is large, the motor has strong, and the high ultrasound gliding aircraft is deemed to be adjacent to space resources and the country. Technical highlights of strategic security. [0003] The trajectory design...

AI Technical Summary

Problems solved by technology

[0008] (1) The traditional offline trajectory optimization is based on a deterministic nominal model, ignoring the uncertainty of the aircraft itself and the environment, so its reference trajectory often lacks robustness, which can easily lead to unpredictable fluctuations in the flight process or deviation from the design direction, thus significantly affecting the mission execution effect, and even threatening the safety of the aircraft itself

[0009] (2) Using technologies such as online trajectory optimization, online tracking guidance, or predictive-correction guidance can compensate for the lack of deterministic reference trajectory to a certain extent, but there are still new design difficulties: in order to meet real-time requirements, online trajectory optimization usually uses At the cost of sacrificing part of the trajectory optimality, but considering the limitation of the amount of ammunition-loaded consumables, the optimal trajectory design is still very necessary

[0010] (3) The calculation speed of online tracking guidance is fast but the guidance accuracy is low, and the prediction-correction guidance accuracy is high but relies heavily on computing power. The hybrid guidance of the two is an improved method under the existing framework, but it is not suitable for trajectory robust design and calculation resources. The configuration lacks fundamental improvements, and its limited correction capabilities limit the performance of the aircraft

[0011] (4) In the existing technology, the research on robust intelligent trajectory planning and guidance considering uncertainty has not yet attracted attention, and in the face of complex multi-source uncertain reentry trajectory optimization problems, there is a lack of high-fidelity robust dynamic trajectory optimization models and Multi-condition robust trajectory design data support

In the face of complex multi-source uncertain reentry trajectory optimization problems, there is a lack of high-fidelity robust dynamic trajectory optimization models and multi-condition robust trajectory design data support

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