In order to solve the problems of high labor intensity, high safety risk and low efficiency of manual loading and unloading under high temperature and high noise environments, this paper designs a loading and unloading control system based on the 3D high-precision vision guidance technology with PLC equipment as the control platform and a six-axis industrial robot as the flexible drive source, and constructs the position servo mathematical model of the unloading equipment under the perturbed working condition, and utilizes the fuzzy neural network PID (FNN-) PID) control algorithm to realize the position control optimization of the loading and unloading equipment. the output parameters \(K_{p}\) , \(T_{i}\) and \(T_{d}\) of the FNN-PID control algorithm can adaptively change the output values based on the fuzzy rule-base with the change of inputs, and it can inhibit the swing angle of the lanyard from 12 degrees to be stabilized at 0 degrees within 24s. Nearby, the tracking effect and anti-swing effect are significantly better than FPID control. This paper adopts the robot vision guidance unloading, so that the unloading control system has obvious improvement in the guiding speed and accuracy, and has high engineering application value.
