Multi-target sliding mode trajectory tracking control algorithm based on BP neural network

The invention discloses a BP neural network-based multi-target sliding mode trajectory tracking control algorithm. The algorithm specifically comprises the following steps of S1, building a vehicle dynamics model; s2, designing a sliding mode surface based on the actual pose deviation motion state equation of the vehicle, and realizing that a sliding mode control algorithm can perform tracking control on multiple targets; s3, designing a sliding mode reaching law based on the BP neural network, and enhancing the adaptability of sliding control; s4, based on a BP neural network-based multi-target sliding mode control algorithm, trajectory tracking is realized by controlling the front wheel turning angle of the vehicle; the invention relates to the technical field of automatic driving rail vehicle trace tracking control. According to the multi-target sliding mode trajectory tracking control algorithm based on the BP neural network, a self-tuning system of sliding mode reaching law parameters is designed based o