Design and simulation of adaptive control system for telescopic pipeline robot

摘要

When continuous tubing encounters excessive frictional resistance in the horizontal section and cannot reach its predetermined position, or self-locking occurs, drag reduction measures such as a pipeline traction robot can be utilised. By controlling the speed and traction force of the robot, the ultimate downstream depth of the continuous tubing can be increased, allowing it to reach its intended operating position. To address the speed regulation and error suppression issues of the downhole traction robot control system, a fuzzy neural network-based proportional-integral-differential (PID) controller was designed and simulated in Simulink. The results demonstrate that the downhole tractor control system with a fuzzy neural network PID controller has superior dynamic and static performance, with 61% less overshoot and 47.5% shorter adjustment time. This indicates high robustness and improved control of the pipeline robot, enabling the continuous tubing to reach its predetermined operating position in a more stable, accurate, and efficient manner.