Automation of Directional Drilling--Novel Trajectory Control Algorithms for RSS

2010 ◽  
Author(s):  
Justo Matheus ◽  
Siva Naganathan
Keyword(s):  
Trajectory Control ◽  
Control Algorithms ◽  
Directional Drilling

Observer‐based trajectory control for directional drilling process

2021 ◽  
Author(s):  
Zhen Cai ◽  
Xuzhi Lai ◽  
Min Wu ◽  
Luefeng Chen ◽  
Chengda Lu
Keyword(s):  
Trajectory Control ◽  
Drilling Process ◽  
Directional Drilling

Recursive Variable Horizon Trajectory Control for Directional Drilling Using Elliptical Helixes

2011 ◽  
Vol 44 (1) ◽  
pp. 10836-10841 ◽  
Author(s):  
Neilkunal Panchal ◽  
Martin T. Bayliss ◽  
James F. Whidborne
Keyword(s):  
Trajectory Control ◽  
Directional Drilling

scholarly journals Integrated Mobile Robotic Platform Model

2021 ◽  
Vol 31 (4) ◽  
pp. 609-627
Author(s):  
Mikhail V. Chugunov ◽  
Irina N. Polunina ◽  
Alexander G. Divin ◽  
Aleksandra A. Generalova ◽  
Artem A. Nikulin ◽  
...  
Keyword(s):  
Solid Mechanics ◽  
Trajectory Control ◽  
Control Algorithms ◽  
Multi Agent System ◽  
Agricultural Machinery ◽  
Robotic Platform ◽  
Agent System ◽  
Model Control ◽  
Multi Agent ◽  
Software And Hardware

Introduction. The “Smart Agroˮ committee of Research and Education Center “Engineering of the Future” has identified a number of tasks relevant for improving the efficiency of precision, soil-protecting and conservation agriculture. One of these tasks is the development of a digital multi-agent system, which provides a number of services for agricultural enterprises, developers and manufacturers of agricultural machinery. The purpose of the present study is to model an autonomous mobile robotic platform, including the development of software and hardware for trajectory control. Materials and Methods. To solve the problem, there are used modern CAx systems and their applications, the methods of 3D and full-body modeling, and the method of numerical solution of problems in solid mechanics. To expand and improve the standard functionality of CAx-systems (SolidWorks) in the software implementation of trajectory control algorithms, the methods and technologies of programming using API SolidWorks, VisualStudio C++ (MFC, ATL, COM) are used, and to build physical full-scale models ‒ Arduino and fischertechnik platforms. Results. The result of the study is a software and hardware module of trajectory control for an integrated (physical and virtual) model of a mobile robotic platform, which can be provided to the consumer as a service for technology autonomation. For the developed integrated model, control algorithms for various types of trajectories were tested. Discussion and Conclusion. The developed integrated software and hardware model of trajectory control can be used by developers and manufacturers of agricultural machinery, and directly by agro-enterprises for implementing typical technological processes. A feature of the implementation is an open hardware and software interface that provides the integration of mobile robotic platforms based on a digital multi-agent system.

scholarly journals PD CONTROLLER BASED UNMANNED SHIP NAVIGATION

2017 ◽  
Vol 5 (4RACEEE) ◽  
pp. 147-154
Author(s):  
Adinath Jain ◽  
Hari Prasad ◽  
Sujata Dahal ◽  
Rajesh Sudi
Keyword(s):  
Computation Time ◽  
Open Loop ◽  
Trajectory Control ◽  
Pid Controllers ◽  
Control Algorithms ◽  
Adaptive Controllers ◽  
Wave Disturbances ◽  
Unmanned Ship ◽  
Standard Models ◽  
Predictive Controllers

For the improvement of the performance of track keeping of unmanned water vehicle numerous ship models, wave disturbances models and distinct control algorithms has been proposed. Researchers are using variants of PID controllers, Adaptive controllers and Predictive controllers for accurate trajectory control. Being simpler in nature still PID controller are popular in control domain. In this paper we have implemented PD based controller for trajectory control of unmanned vehicle considering all standard models of sea disturbances. Analysis of result obtained using PD control proved that path tracking is more accurate than open loop controller in terms of computation time, complexity and fuel consumption.

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