
FOPID-Controlled Self-Propelled Pipeline Inspection Robot for Internal Mapping of Small-Diameter Pipelines
Author(s) -
Rizwan Aziz Mangi,
Ghulam E Mustafa Abro,
Sufyan Ali Memon,
Aneela Pathan,
Khalil Muhammad Zuhaib,
Maran Marimuthu
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3595951
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Conventional pipeline route mapping systems frequently depend on external sensing technology, like cameras and laser scanners. Although useful in certain situations, these devices are often costly, cumbersome, and significantly vulnerable to environmental factors, such as inadequate lighting and reflecting internal surfaces—particularly in constricted pipelines. These constraints render them inappropriate for small-scale industrial pipes, generally ranging from 3 to 4 inches in diameter. This paper presents a compact and cost-effective Pipeline Route Mapping System (PRMS) that solely uses internal sensing techniques to tackle these difficulties. The design features a self-propelled Pipeline Inspection Robot (PIR) that autonomously traverses restricted pipeline geometries. The robot’s movement is meticulously controlled by a Fractional Order Proportional Integral Derivative (FOPID) controller, chosen for its superior adaptability and resilience in nonlinear and limited settings. The suggested method facilitates the extraction of essential pipeline characteristics, encompassing the identification of transition sites between linear and curved segments, precise alignment of linear sections in accordance with curvature, and interpolation of bends and directional changes. The system has been validated by extensive MATLAB/Simulink simulations and empirical testing, demonstrating its capacity to accurately reconstruct pipeline pathways with minimal sensor hardware. This research facilitates the development of a novel category of economical, compact, and intelligent PIRs that can enhance sophisticated mapping algorithms. Its applicability encompasses several industrial inspection and maintenance contexts, enhancing the safety and efficiency of pipeline infrastructure management.
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