改进的考虑自动驾驶仪动态特性的有限时间滑模导引律

Transducer and Microsystem Technologies（2019）

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Abstract

为减小导弹自动驾驶仪延迟特性对制导精度的影响,考虑到实际战争中制导末段时间很短,推导了考虑导弹动态特性的有限时间收敛的制导数学模型;其次根据滑模控制理论设计了基于该数学模型的导引律;证明了所设计的导引律在制导系统中有限时间稳定;为削弱滑模导引律的抖振现象,利用双曲正切函数改进了导引律.仿真表明:改进的导引律在目标做非机动和机动的情形下均能在有限时间内快速跟踪目标的运动,并保持较高的制导精度.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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