In consideration of the field-of-view(FOV)angle con-straint,this study focuses on the guidance problem with impact time control.A deep reinforcement learning guidance method is given for the missile to obtain the desi...In consideration of the field-of-view(FOV)angle con-straint,this study focuses on the guidance problem with impact time control.A deep reinforcement learning guidance method is given for the missile to obtain the desired impact time and meet the demand of FOV angle constraint.On basis of the framework of the proportional navigation guidance,an auxiliary control term is supplemented by the distributed deep deterministic policy gradient algorithm,in which the reward functions are developed to decrease the time-to-go error and improve the terminal guid-ance accuracy.The numerical simulation demonstrates that the missile governed by the presented deep reinforcement learning guidance law can hit the target successfully at appointed arrival time.展开更多
The guidance strategy is an extremely critical factor in determining the striking effect of the missile operation.A novel guidance law is presented by exploiting the deep reinforcement learning(DRL)with the hierarchic...The guidance strategy is an extremely critical factor in determining the striking effect of the missile operation.A novel guidance law is presented by exploiting the deep reinforcement learning(DRL)with the hierarchical deep deterministic policy gradient(DDPG)algorithm.The reward functions are constructed to minimize the line-of-sight(LOS)angle rate and avoid the threat caused by the opposed obstacles.To attenuate the chattering of the acceleration,a hierarchical reinforcement learning structure and an improved reward function with action penalty are put forward.The simulation results validate that the missile under the proposed method can hit the target successfully and keep away from the threatened areas effectively.展开更多
Split Hopkinson pressure bar(SHPB)was utilized to explore the effects of loading strain rate on the dynamic compressing strength of the titanium alloy lattice material.Results reveal that the yield strength of alloy l...Split Hopkinson pressure bar(SHPB)was utilized to explore the effects of loading strain rate on the dynamic compressing strength of the titanium alloy lattice material.Results reveal that the yield strength of alloy lattice material reaches 342 MPa initially and then drops to 200 MPa before it rebounds to 252 MPa while the loading strain rate correspondingly increases from the static value 1401/s to 2084/s.Numerical simulations were then carried out to explore the possible reason underlying.Results show that the lattice structure changed the stress distribution and caused significate stress concentration at finite strain with high strain rate.It is believed that the strain rate strengthening effect and layer-wise failure mode are the main reasons of the above mechanical properties change.展开更多
基金supported by the National Natural Science Foundation of China(62003021,62373304)Industry-University-Research Innovation Fund for Chinese Universities(2021ZYA02009)+2 种基金Shaanxi Qinchuangyuan High-level Innovation and Entrepreneurship Talent Project(OCYRCXM-2022-136)Shaanxi Association for Science and Technology Youth Talent Support Program(XXJS202218)the Fundamental Research Funds for the Central Universities(D5000210830).
文摘In consideration of the field-of-view(FOV)angle con-straint,this study focuses on the guidance problem with impact time control.A deep reinforcement learning guidance method is given for the missile to obtain the desired impact time and meet the demand of FOV angle constraint.On basis of the framework of the proportional navigation guidance,an auxiliary control term is supplemented by the distributed deep deterministic policy gradient algorithm,in which the reward functions are developed to decrease the time-to-go error and improve the terminal guid-ance accuracy.The numerical simulation demonstrates that the missile governed by the presented deep reinforcement learning guidance law can hit the target successfully at appointed arrival time.
基金supported by the National Natural Science Foundation of China(62003021,91212304).
文摘The guidance strategy is an extremely critical factor in determining the striking effect of the missile operation.A novel guidance law is presented by exploiting the deep reinforcement learning(DRL)with the hierarchical deep deterministic policy gradient(DDPG)algorithm.The reward functions are constructed to minimize the line-of-sight(LOS)angle rate and avoid the threat caused by the opposed obstacles.To attenuate the chattering of the acceleration,a hierarchical reinforcement learning structure and an improved reward function with action penalty are put forward.The simulation results validate that the missile under the proposed method can hit the target successfully and keep away from the threatened areas effectively.
文摘Split Hopkinson pressure bar(SHPB)was utilized to explore the effects of loading strain rate on the dynamic compressing strength of the titanium alloy lattice material.Results reveal that the yield strength of alloy lattice material reaches 342 MPa initially and then drops to 200 MPa before it rebounds to 252 MPa while the loading strain rate correspondingly increases from the static value 1401/s to 2084/s.Numerical simulations were then carried out to explore the possible reason underlying.Results show that the lattice structure changed the stress distribution and caused significate stress concentration at finite strain with high strain rate.It is believed that the strain rate strengthening effect and layer-wise failure mode are the main reasons of the above mechanical properties change.
