Model Predictive Control Strategy Based on Improved Trajectory Extension Model for Deviation Correction in Vertical Drilling Process
Author(s) -
Dian Zhang,
Min Wu,
Luefeng Chen,
Chengda Lu,
Weihua Cao,
Feng Wang
Publication year - 2020
Publication title -
ifac-papersonline
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 72
eISSN - 2405-8971
pISSN - 2405-8963
DOI - 10.1016/j.ifacol.2020.12.331
Subject(s) - trajectory , drilling , model predictive control , process (computing) , control theory (sociology) , position (finance) , directional drilling , geology , computer science , extension (predicate logic) , measurement while drilling , controller (irrigation) , control (management) , engineering , mechanical engineering , artificial intelligence , finance , astronomy , economics , operating system , agronomy , biology , programming language , physics
Vertical drilling system is widely used in deep geological exploration. As only inclination angle is considered in conventional vertical drilling systems, which decreases the quality of drilling trajectory, especially in geological drilling. In this paper, a model predictive control strategy based on improved trajectory extension model is provided, and it aims to reduce the position deviation and inclination angle of the drilling trajectory in vertical drilling process. An improved trajectory extension model is established by considering both attitude dynamic and space movement of bottom hole assembly under ground in vertical drilling process; and then, in order to deal with control constraints directly, a model predictive controller is provided based on the improved trajectory extension model. Simulation results of deviation correction are presented for validating the proposed strategy.
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