Intelligent control method of end effector of food sorting robot based on improved inversion control

Abstract

Objective: Solve the problems of poor positioning accuracy and low efficiency of end effectors in the sorting process of parallel food sorting robots. Methods: An intelligent control of the end-effector of a parallel food sorting robot combining fuzzy system, fuzzy neural network and inverse control algorithm was proposed. The modeling information was approximated by the fuzzy system, the unmodeled information was approximated and predicted by the fuzzy neural network, and the inversion control completed the control output. Finally, the experimental verification is carried out. Results: Compared with the traditional control method, the proposed control method had good tracking accuracy and control efficiency of the end effector, the error of the end effector was less than 0.3 mm, and the sorting efficiency reached 1.99 s-1. Conclusion: This control method can achieve accurate, efficient and stable position tracking.

Keywords

• parallel food sorting robot
• end effector
• backstepping control algorithm
• fuzzy neural network
• fuzzy system