基于改进反演控制的食品分拣机器人末端执行器智能控制方法

目的:解决并联食品分拣机器人分拣过程中存在的末端执行器定位精度差、效率低等问题。方法:提出一种将模糊系统、模糊神经网络和反演控制算法相结合用于并联食品分拣机器人末端执行器的智能控制。建模信息由模糊系统逼近,未建模信息由模糊神经网络逼近和预测,反演控制完成控制输出,最后进行实验验证。结果:与传统控制方法相比,所提控制方法具有良好的末端执行器跟踪精度和控制效率,末端执行器误差小于0.3mm,分选效率达到1.99个/s。结论:该控制方法可以实现准确、高效和稳定的位置跟踪。

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

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 reached1.99s-1.Conclusion: This control method can achieve accurate, efficient and stable position tracking.