The invention discloses a
silage corn harvester header height real-time automatic lifting
system based on deep
reinforcement learning, which comprises an angle sensor, a DDPG controller and a
PID controller, the angle sensor can convert angle data between a header and the ground into an
electric signal and output the
electric signal to the DDPG controller, the input of the DDPG controller is a target value, an actual value and a deviation value, and the
PID controller is used for controlling the real-time automatic lifting of the header height of the
silage corn harvester. And an experience
pool is added for the DDPG
algorithm. The DDPG controller outputs a
signal to the
PID controller, the PID controller is provided with two
signal input ends which are used for inputting an action
signal and a deviation value respectively, the output end of the PID controller is connected with the hydraulic
system, the header is controlled to ascend and descend through the hydraulic
system, a target value is given by the outside, an actual value is fed back by the angle sensor, and the deviation value is the difference value between the target value and the actual value. The header lifting device has the advantages that automatic lifting of the header is completely controlled by a DDPG
algorithm and a PID controller, and high
automation of lifting of the header is achieved.