Title: Design and simulation of adaptive control system for telescopic pipeline robot

Authors: Jie Zheng; Yangjie Bai; Yong Zheng; Yarong Zhang; Zhenzhen Li

Addresses: School of Mechanical Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China; School of Power and Energy, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China; Xi'an Special Equipment Inspection Institute, Xi'an, Shaanxi 710065, China ' School of Mechanical Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China ' Baoji Oilfield Machinery Co., Ltd., Baoji, Shaanxi 721015, China; National Engineering Research Center for Oil & Gas Drilling Equipment, Baoji, Shaanxi 721015, China ' School of Science, Xi'an University of Architecture and Technology, Xi'an, Shaanxi 710055, China; School of Power and Energy, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China; Xi'an Special Equipment Inspection Institute, Xi'an, Shaanxi 710065, China ' School of Mechanical Engineering, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China

Abstract: 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.

Keywords: pipeline robot; control system; fuzzy neural network PID; control system simulation; high robustness.

DOI: 10.1504/IJMMS.2023.132026

International Journal of Mechatronics and Manufacturing Systems, 2023 Vol.16 No.1, pp.55 - 82

Received: 11 Nov 2022
Accepted: 17 Apr 2023
Published online: 06 Jul 2023 *

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