Cognitive interference decision method for air defense missile fuze based on reinforcement learning

Huang, Dingkun; Yan, Xiaopeng; Dai, Jian; Wang, Xinwei; Liu, Yangtian

doi:10.1016/j.dt.2023.04.002

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…Owing to different targets, the best damage mode was different. The mapping relationship between the target characteristic value and the detonation mode was constructed from [20,[64][65][66][67][68][69][70][71][72][73][74][76][77][78][79][80] and the measured data. The mapping relationship was used to optimize the parameters of the detonation controller to obtain the optimal controller.…”

Section: Burst Point Control Of a Penetration Fuzementioning

confidence: 99%

Innovation of control technology for smart fuzes: precise detonation and efficient damage via a ternary cascade controller

Liu,

Li,

et al. 2024

Front. Phys.

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The traditional theory of dynamic open-loop control of fuzes has been unable to satisfy the demand for smart fuze control. After analyzing time–space recognition and process control as the basis of fuze detonation control, three key issues of smart fuze control are summarized herein. Furthermore, three types of controllers are constructed, namely, detection, state, and detonation controllers, which achieve the precise detonation control of ammunition under the interference of complex multi-physics environments, ensuring efficient damage to the target. Based on the above-mentioned controllers, the design theory of the ternary cascade control of the smart fuze is established. In addition, the technical system of the ternary cascade control theory is reviewed, and the latest progress in control strategy design, environment modeling, target modeling, and other fields is summarized in detail. Finally, the development demands and technology trends in intelligent fuze control technology for future intelligent warfare are explored.

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