The invention discloses a microwave drying PID (proportion integration differentiation) control method based on an increment improved BP (back propagation) neural network, selecting a three-layer BP neural network as a protomodel and combining incremental learning, an L-M (Levenberg-Marquardt) optimization algorithm, a BP neural network and PID control to realize online adjustment of PID control parameters. The method comprises the following steps: firstly carrying out offline system identification on a neural network by adopting the actual production data in a microwave drying process as training data, comparing the output value of the network with the measured value until the mean square error of network training meets the requirement, determining weight and threshold for each layer of the network, and carrying out online dynamic adjustment on the PID control parameters by taking parameters of a controlled object which are measured in the actual production process as the input of the neural network, wherein the output of the neural network is namely parameters of a PID controller Kp, Ki and Kd.