Jie Song

Increasingly complex combat missions impose higher demands on missile guidance performance, making the development of strapdown miniature missiles an important trend. Addressing the integrated guidance and control (IGC) problem for strapdown miniature missiles with impact angle and field of view (FOV) constraints under bearing‐only measurements, this paper proposes a deep reinforcement learning (DRL)‐based IGC approach. The missile's kinematic and dynamic models are formulated as a discrete‐time Markov decision process (MDP). The impact‐angle error and body‐line‐of‐sight (BLOS) angle are selected as the state variables, and a corresponding reward function is constructed. Policy and value networks are established accordingly, with fin deflection serving as the policy action. Building on proximal policy optimization (PPO), this paper introduces a segment‐wise advantage sampling strategy and a sliding‐window data update method. An elite trajectory buffer is maintained to guide training, and the training data are refreshed in a sliding‐window manner. The training results indicate that the improved algorithm provides more stable and efficient learning under the tested conditions. Policy test results indicate that the proposed IGC approach maintains excellent guidance performance under varying conditions, exhibiting strong robustness and a capture region comparable to or larger than those of existing guidance laws while using less measurement information. These results validate the effectiveness and superiority of the presented method.

With the evolution of efficient gas energy utilization technologies, nozzle-based rear ejection has emerged as a promising approach for recoil reduction in launch systems. This paper systematically investigates the influence of nozzle geometric parameters on the nozzle gas flow field and the recoil reduction performance of the gun through numerical simulation. First, a one-dimensional two-phase flow internal ballistics model for a gun equipped with a rear-ejecting nozzle is developed, along with theoretical methods for calculating the thrust and recoil metrics. Based on this, the unsteady flow field of the nozzle is simulated using a two-dimensional axisymmetric computational fluid dynamics model, employing the gas pressure at the vent obtained from internal ballistic calculation as inlet boundary condition. Pressure tests and flow field visualization experiments validate the accuracy of the simulations. By analyzing the nozzle flow field characteristics under various geometric parameters, the effects of expansion angle, cone length, cylindrical length, and vent position are quantified. Results indicate that recoil reduction efficiency individually peaks at a 5° expansion angle or a 126 mm cone length, reaching 55.7%. Both maximum thrust and recoil reduction efficiency are negatively correlated with cylindrical length and vent position. Furthermore, sensitivity analysis based on orthogonal design reveals that cone length and cylindrical length are the dominant factors determining maximum thrust and recoil reduction efficiency, respectively. From a fluid dynamics perspective, this study provides an effective analytical framework and valuable design guidance for optimizing nozzle configurations to enhance recoil reduction performance.

The symmetry-breaking vibrational response of a gun muzzle, induced by the thermo–mechanical coupling effect under continuous firing, is a critical factor degrading shooting accuracy. This study investigates the nonlinear influence of chamber pressure variation on this asymmetric dynamic response. A thermo–mechanically coupled interaction model between a 5.8 mm bullet and its barrel is established using nonlinear finite element methods, incorporating experimentally measured pressure data. The kinematic state of the muzzle under a heated barrel condition (after 90 rounds) is systematically analyzed across five chamber pressure levels (90% to 110% of standard). The results reveal a highly nonlinear relationship between chamber pressure and muzzle vibration. Surprisingly, the maximum values for comprehensive radial displacement (10.601 × 10⁻³ mm), velocity (0.327 m/s), acceleration (11.083 m/s²), swing angle (0.192 mrad), and swing angular velocity (9.166 rad/s) occurred at the 100% standard pressure, not the highest pressure. Reducing the pressure to 90% of the standard effectively suppressed these asymmetric vibrations, with magnitudes declining by 84.28% to 95.49%. This indicates that the symmetry of the muzzle’s dynamic state is disrupted under thermal effects, and strategically lowering chamber pressure can restore a more symmetric and stable launch attitude, thereby enhancing accuracy. This study elucidates the nonlinear correlation mechanism between pressure and thermally induced asymmetric vibration, providing a novel perspective for optimizing the accuracy of rapid-fire weapons based on symmetry principles.

The symmetry-breaking vibrational response of a gun muzzle, induced by thermo-mechanical coupling effect under continuous firing, is a critical factor degrading shooting accuracy. This study investigates the nonlinear influence of chamber pressure variation on this asymmetric dynamic response. A thermo-mechanically coupled interaction model between a 5.8 mm bullet and its barrel is established using nonlinear finite element methods, incorporating experimentally measured pressure data. The kinematic state of muzzle under a heated barrel condition (after 90 rounds) was systematically analyzed across five chamber pressure levels (90% to 110% of standard). The results reveal a highly nonlinear relationship between chamber pressure and muzzle vibration. Surprisingly, the maximum values for comprehensive radial displacement (10.601×10⁻³ mm), velocity (0.327 m/s), acceleration (11.083 m/s²), swing angle (0.192 mrad), and swing angular velocity (9.166 rad/s) occurred at the 100% standard pressure, not the highest pressure. Reducing the pressure to 90% of the standard effectively suppressed these asymmetric vibrations, with magnitudes declining by 84.28% to 95.49%. This indicates that the symmetry of the muzzle's dynamic state is disrupted under thermal effects, and strategically lowering chamber pressure can restore a more symmetric and stable launch attitude, thereby enhancing accuracy. This study elucidates the nonlinear correlation mechanism between pressure and thermally induced asymmetric vibration, providing a novel perspective for optimizing the accuracy of rapid-fire weapons based on symmetry principles.

Aramid fibre has become a critical material for individual soft body armour due to its lightweight nature and exceptional impact resistance. To investigate its energy absorption mechanism, quasi-static and dynamic tensile experiments were conducted on Kevlar^® 29 plain-woven fabric using a universal material testing machine and a Split Hopkinson Tensile Bar (SHTB) apparatus. Tensile mechanical responses were obtained under various strain rates. Fracture morphology was characterised using scanning electron microscopy (SEM) and ultra-depth three-dimensional microscopy, followed by an analysis of microstructural damage patterns. Considering the strain rate effect, a viscoelastic constitutive model was developed. The results indicate that the tensile mechanical properties of Kevlar^® 29 plain-woven fabric are strain-rate dependent. Tensile strength, elastic modulus, and toughness increase with strain rate, whereas fracture strain decreases. Under quasi-static loading, the fracture surface exhibits plastic flow, with slight axial splitting and tapered fibre ends, indicating ductile failure. In contrast, dynamic loading leads to pronounced axial splitting with reduced split depth, simultaneous rupture of fibre skin and core layers, and fibrillation phenomena, suggesting brittle fracture characteristics. The modified three-element viscoelastic constitutive model effectively captures the strain-rate effect and accurately describes the tensile behaviour of the plain-woven fabric across different strain rates. These findings provide valuable data support for research on ballistic mechanisms and the performance optimisation of protective materials.

The primary motivation of this study is to develop a sensor-less, easily controlled, and passively adaptive robotic gripper. A back-drivable pneumatic underactuated robotic gripper (PURG), based on the pneumatic cylinder and underactuated finger mechanism, is presented to accomplish the above goals. A feedforward grasping force control method, based on the learned kinematics of the underactuated finger mechanism, is proposed to achieve sensor-less grasping force control. To enhance the grasping force control accuracy, a state-based actuating force modeling method is presented to compensate the hysteresis error which exists in the transmission mechanism. Actuating force control experiment is performed to validate the effectiveness of the state-based actuating pressure modeling method. Results reveal that compared with the non-state-based modeling method, the proposed state-based actuating force modeling method could reduce the modeling error and control error by about 37.0% and 77.2%, respectively. Results of grasping experiments further reveal that grasping force could be accurately controlled by the state-based feedforward control model in a sensor-less approach. Adaptive grasping experiments are performed to exhibit the effectiveness of the sensor-less grasping force control approach.