Control Algorithms For Robot Manipulators To Optimize Paper Flow In Printing Processes

Abstract

The article examines the problem of optimizing the processes of transferring, sorting, and packaging paper sheets along a conveyor in printing enterprises using a robot manipulator. The main issue highlighted is the lack of mathematically grounded control algorithms that properly link conveyor speed, paper flow intensity, and the robot manipulator’s operational cycle. As a result, paper jams, robot idle time, and defect rates increase. In the article, the movement of paper on the conveyor is expressed using basic differential equations, while the flow intensity is modeled through the M/M/1 queueing theory framework. Based on the kinematic and dynamic models of the robot manipulator, a jerk-limited trajectory planning algorithm is proposed. Simulation results conducted in the MATLAB/Simulink environment show that the proposed algorithm keeps the load coefficient of the conveyor–robot system around ρ = 0.73, reduces the queue length from 20 to 2.7 items, and decreases the frequency of paper jams by up to 40%.