scholarly journals Adaptive steering control for an azimuth thrusters-based autonomous vessel

2019 ◽  
Vol 19 (sup1) ◽  
pp. 76-91 ◽  
Author(s):  
M. Bibuli ◽  
A. Odetti ◽  
E. Zereik
2009 ◽  
Vol 129 (7) ◽  
pp. 1389-1396 ◽  
Author(s):  
Misawa Kasahara ◽  
Yuki Kanai ◽  
Ryoko Shiraki ◽  
Yasuchika Mori

2021 ◽  
Vol 11 (6) ◽  
pp. 2743-2761
Author(s):  
Caetano P. S. Andrade ◽  
J. Luis Saavedra ◽  
Andrzej Tunkiel ◽  
Dan Sui

AbstractDirectional drilling is a common and essential procedure of major extended reach drilling operations. With the development of directional drilling technologies, the percentage of recoverable oil production has increased. However, its challenges, like real-time bit steering, directional drilling tools selection and control, are main barriers leading to low drilling efficiency and high nonproductive time. The fact inspires this study. Our work aims to contribute to the better understanding of directional drilling, more specifically regarding rotary steerable system (RSS) technology. For instance, finding the solutions of the technological challenges involved in RSSs, such as bit steering control, bit position calculation and bit speed estimation, is the main considerations of our study. Classical definitions from fundamental physics including Newton’s third law, beam bending analysis, bit force analysis, rate of penetration (ROP) modeling are employed to estimate bit position and then conduct RSS control to steer the bit accordingly. The results are illustrated in case study with the consideration of the 2D and 3D wellbore scenarios.


Author(s):  
Jinxiang Wang ◽  
Zhenwu Fang ◽  
Mengmeng Dai ◽  
Guodong Yin ◽  
Jingjing Xia ◽  
...  

A human-machine shared steering control is presented in this paper for tracking large-curvature path, considering uncertainties of driver’s steering characteristics. A driver-vehicle-road (DVR) model is proposed in which uncertain characteristic parameters are defined to describe the human driver’s steering behaviors in tracking large-curvature path. Then the radial basis function neural network (RBF) is used to estimate parameters of different drivers’ characteristics and to obtain the boundaries of these parameters. Parameter uncertainties of the driver’s steering characteristics and time-varying vehicle speed of the DVR model are handled with the Takagi-Sugeno (T-S) fuzzy logic. And these parameter uncertainties are considered in the design of the shared steering controller. Then based on the DVR model, a T-S fuzzy full-order dynamic compensator with D-pole assignment is designed to assist driver’s steering for tracking path with large curvature. Simulation results show that the proposed controller can provide individual levels of steering assistance in path following according to driver’s proficiency, and can improve driving comfort significantly.


2021 ◽  
Vol 22 (4) ◽  
pp. 979-992
Author(s):  
Wu Liang ◽  
Ejaz Ahmac ◽  
Muhammad Arshad Khan ◽  
Iljoong Youn

Author(s):  
Shihuan Li ◽  
Lei Wang

For L4 and above autonomous driving levels, the automatic control system has been redundantly designed, and a new steering control method based on brake has been proposed; a new dual-track model has been established through multiple driving tests. The axle part of the model was improved, the accuracy of the transfer function of the model was verified again through acceleration-slide tests; a controller based on interference measurement was designed on the basis of the model, and the relationships between the controller parameters was discussed. Through the linearization of the controller, the robustness of uncertain automobile parameters is discussed; the control scheme is tested and verified through group driving test, and the results prove that the accuracy and precision of the controller meet the requirements, the robustness stability is good. Moreover, the predicted value of the model fits well with the actual observation value, the proposal of this method provides a new idea for avoiding car out of control.


2020 ◽  
Vol 1452 ◽  
pp. 012012 ◽  
Author(s):  
Eric Simley ◽  
Paul Fleming ◽  
Jennifer King

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