Abstract: Control circuits for reducing electromagnetic radiation and control methods thereof, and isolated power supply systems are disclosed. The control circuit includes: an inverter circuit, a first adaptive control circuit, a first oscillation circuit and a first driving circuit, the inverter circuit outputs a first voltage signal and a second voltage signal; the first oscillation circuit generates and outputs a first oscillation signal, a first sampling end of the first adaptive control circuit couples to the first voltage signal, a second sampling end of the first adaptive control circuit couples to the second voltage signal, an input end of the first adaptive control circuit connects with an output end of the first oscillation circuit, an output end of the first adaptive control circuit connects with an input end of the first driving circuit, and an output end of the first driving circuit connects with a control end of the inverter circuit.

Abstract: The present invention discloses a method for UAV path planning in urban airspace based on a safe reinforcement learning (RL) algorithm called shield-DDPG, which combines a shield model with a DDPG algorithm and pertains to the field of UAV technologies. The method takes an attractive force from the destination point into account when an action is selected, which improves the convergence speed of the algorithm and also improve the efficiency of UAV path planning. More importantly, the method provided by the present invention can effectively verify safety of an action in terms of the air collision risk and the ground impact risk, and ensure that a final output of the algorithm is a safe optimal solution. Therefore, the present invention can effectively solve the problem that when the RL algorithm is used for UAV path planning, it is difficult to ensure the safety of the learning or execution process due to the lack of hard constraints.

Abstract: The present invention discloses a method for UAV path planning in urban airspace based on a safe reinforcement learning (RL) algorithm called shield-DDPG, which combines a shield model with a DDPG algorithm and pertains to the field of UAV technologies. The method takes an attractive force from the destination point into account when an action is selected, which improves the convergence speed of the algorithm and also improve the efficiency of UAV path planning. More importantly, the method provided by the present invention can effectively verify safety of an action in terms of the air collision risk and the ground impact risk, and ensure that a final output of the algorithm is a safe optimal solution. Therefore, the present invention can effectively solve the problem that when the RL algorithm is used for UAV path planning, it is difficult to ensure the safety of the learning or execution process due to the lack of hard constraints.