状态预测神经网络控制应用于小型可回收火箭

doi:10.7527/S1000-6893.2018.22286

Abstract

Abstract: With the advent of commercial aerospace exploration, research on reusable vehicles has received extensive attention. Some reusable rockets developed by commercial space companies represented by SpaceX have exhibited unprecedented competitiveness. To develop reusable rocket technology, LinkSpace has developed a small verifying rocket called RLV-T3, and gradually mastered the Vertical Takeoff and Veratical Landing (VTVL) technology through hundreds of tests on this verification machine. This paper mainly introduces the State Prediction Neural Network Control (SPNNC) algorithm, a thrust control technique in VTVL technology. The algorithm has strong robustness, wide application range, and easy adjustment of control parameters. This paper describes the principle of the algorithm in detail and simulates both SISO and MIMO systems using Simulink. At the same time, this paper discusses in detail the test of the SPNNC applied to the RLV-T3, including the basic characteristics of the small reusable rocket, control difficulties, existing problems, the flight curve of the physical quantities, and test conclusions. It has been verified by experiments that the SPNNC has good control performance, and the small recyclable rocket verification machine named RLV-T3 based on SPNNC can safely implement the whole process of vertical takeoff, ballistic flight, air hovering, and soft landing recovery.

Key words: neural network control, intelligent control, state prediction, reusable rocket, rocket recovery, commercial aerospace

CLC Number:

CHEN Shuzhao, CHU Longfei, YANG Xiumei, CAI Dehuai. Application of state prediction neural network control algorithm in small reusable rocket[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019, 40(3): 322286-322286.

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Application of state prediction neural network control algorithm in small reusable rocket

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