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Trajectory tracking control for rotary steerable systems using interval type-2 fuzzy logic and reinforcement learning
Zhang, Chi1,2; Zou, Wei1,3; Cheng, Ningbo1; Gao, Junshan2
Source PublicationJOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
2018
Volume355Issue:2Pages:803-826
SubtypeArticle
AbstractRotary steerable system (RSS) is a directional drilling technique which has been applied in oil and gas exploration under complex environment for the requirements of fossil energy and geological prospecting. The nonlinearities and uncertainties which are caused by dynamical device, mechanical structure, extreme downhole environment and requirements of complex trajectory design in the actual drilling work increase the difficulties of accurate trajectory tracking. This paper proposes a model-based dual-loop feedback cooperative control method based on interval type-2 fuzzy logic control (IT2FLC) and actor-critic reinforcement learning (RL) algorithms with one-order digital low-pass filters (LPF) for three-dimensional trajectory tracking of RSS. In the proposed RSS trajectory tracking control architecture, an IT2FLC is utilized to deal with system nonlinearities and uncertainties, and an online iterative actor-critic RL controller structured by radial basis function neural networks (RBFNN) and adaptive dynamic programming (ADP) is exploited to eliminate the stick-slip oscillations relying on its approximate properties both in action function (actor) and value function (critic). The two control effects are fused to constitute cooperative controller to realize accurate trajectory tracking of RSS. The effectiveness of our controller is validated by simulations on designed function tests for angle building hole rate and complete downhole trajectory tracking, and by comparisons with other control methods. (c) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
WOS HeadingsScience & Technology ; Technology ; Physical Sciences
DOI10.1016/j.jfranklin.2017.12.001
WOS KeywordDIRECTIONAL DRILLING SYSTEMS ; NONLINEAR-SYSTEMS ; FEEDBACK-CONTROL ; DESIGN ; PERFORMANCE
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundations of PR China(51405484 ; Project of Development in Tianjin for Scientific Research Institutes ; Tianjin Government(16PTYJGX00050) ; 61773374)
WOS Research AreaAutomation & Control Systems ; Engineering ; Mathematics
WOS SubjectAutomation & Control Systems ; Engineering, Multidisciplinary ; Engineering, Electrical & Electronic ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000425496700009
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21956
Collection精密感知与控制研究中心_精密感知与控制
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Harbin Univ Sci & Technol, Sch Automat, Harbin 150080, Heilongjiang, Peoples R China
3.CASIA Co Ltd, Tianjin Intelligent Technol Inst, Tianjin 300309, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Chi,Zou, Wei,Cheng, Ningbo,et al. Trajectory tracking control for rotary steerable systems using interval type-2 fuzzy logic and reinforcement learning[J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS,2018,355(2):803-826.
APA Zhang, Chi,Zou, Wei,Cheng, Ningbo,&Gao, Junshan.(2018).Trajectory tracking control for rotary steerable systems using interval type-2 fuzzy logic and reinforcement learning.JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS,355(2),803-826.
MLA Zhang, Chi,et al."Trajectory tracking control for rotary steerable systems using interval type-2 fuzzy logic and reinforcement learning".JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 355.2(2018):803-826.
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