Abstract:Aiming at the actual demand of omnidirectional chassis control, an intelligent control method based on fuzzy immune neural network PID algorithm is proposed to set parameters of the path tracking controller of the chassis to realize the precise motion control of the chassis. According to the structural characteristics of the neural network algorithm and the fuzzy algorithm, the fuzzy neural network model is established and the model is trained by the method of error back propagation. The immune algorithm is used to determine the learning rate and then, the dynamic tuning of the PID parameters is realized. After that, the kinematic model of the chassis is established. Then, based on Matlab platform, the relevant algorithm is simulated. Finally, the neural network model is established and trained via the Tensorflow structure under the Linux Ubuntu system and the algorithm is then implemented. When the chassis carries out trajectory tracking in different directions at a 5 m/s speed, the maximum error of the process is 4.88 cm, the average error is 0.25 cm. Simulations and experiments both show that the algorithm can effectively control the chassis to meet requirements of thecontrol of the omnidirectional chassis.