AGV pallet fork speed control method based on MPSO optimization neural network

The invention discloses an AGV pallet fork speed control method based on an MPSO optimization neural network. The AGV pallet fork speed control method comprises the steps that a sensor is installed; the sensor comprises a piezoelectric sensor, a photoelectric encoder and a stay wire encoder; processing data; the data comprises the load of the prong, the running speed of the vehicle, the current height Fh of the prong, the expected lifting speed S and the actual lifting speed Sreal; neural network design and training: designing a one-dimensional neural network; adopting an MPSO algorithm to optimize parameters of the neural network; and the trained neural network is adopted to control the fork tooth speed. By adopting the technical scheme, the difference between the predicted speed and the actual speed of the fork tooth of the AGV is minimized by utilizing the fitting capability of the neural network, so that the actual lifting speed of the fork tooth can be predicted by the AGV under various speed and load co