This paper is concerned with tool attitude control of directional drilling systems, which plays a key role in guaranteeing desired drilling trajectory. The coupling of inclination and azimuth motions are taken into ac...
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ISBN:
(纸本)9781728102634
This paper is concerned with tool attitude control of directional drilling systems, which plays a key role in guaranteeing desired drilling trajectory. The coupling of inclination and azimuth motions are taken into account in the motion model, where the azimuth one involves some time-varying parameters. To ensure satisfactory control precision, an output-feedback compensation control scheme is developed based on a motion model established from Taylor expansion. Stability analysis is sequentially made for the resulting inclination and azimuth closed-loop system. At last, some simulations show that the compensation controller can achieve higher control accuracy than a proportional integral controller.
The goal of unmanned aerial vehicle (UAV) image mosaicing is to create natural-looking mosaics free of artifacts due to the parallax of the image and relative camera motion. UAV remote sensing is a low-altitude techno...
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ISBN:
(数字)9781728163741
ISBN:
(纸本)9781728163758
The goal of unmanned aerial vehicle (UAV) image mosaicing is to create natural-looking mosaics free of artifacts due to the parallax of the image and relative camera motion. UAV remote sensing is a low-altitude technology and the UAV imaged scene is not effectively planar, yielding parallax on images. In this paper, we apply local homography to match UAV images, which can reduce misalignment artifacts or “ghosting” in the results compared with 2D projective transforms or global homography. In addition, when an object in three dimensions is mapped to an image plane, different surfaces have different projections. These projections vary with the viewpoint in a sequence of UAV images, which still causes artifacts near some tall buildings if we only use local homography. We propose a novel stitching method based multi-region local projection deformation, that divides the overlapping regions of input images into several regions, then meshes image to calculate local projections by partitioned regions. Specifically, we use a strategy where multiple regions have different weights for calculating local projections, which can significantly reduce ghosting due to these projections vary with the viewpoint and parallax. The benefits of the proposed approach are demonstrated using a variety of challenging cases.
Given emotion is important in maintaining mental and physical well-being. A multi-objective weighted reinforcement learning (MOW-RL) decision method is proposed to execute emotion regulation in human-robot interaction...
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ISBN:
(纸本)9781728102634
Given emotion is important in maintaining mental and physical well-being. A multi-objective weighted reinforcement learning (MOW-RL) decision method is proposed to execute emotion regulation in human-robot interaction. The goal of emotion regulation is to minimize the cost of executing the service while eliminate user's negative emotions or maintain user's positive emotions. Considering the coordination problem of two objectives, fuzzy analytic hierarchy process (FAHP) is used to calculate the weight of each target reward and punishment function under different conditions. In addition, the influence factors of different personality on the difficulty level of emotion transfer are calculated by FAHP. Experiments are performed by 20 experimenters in the laboratory scenario, from which the results show that experimenters' satisfaction is 2.3, which is close to satisfaction.
Continuous casting is an important process in iron and steel production. In continuous casting process, in order to improve the control precision of mould level under steady-state working condition, and to suppress la...
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ISBN:
(纸本)9781728102634
Continuous casting is an important process in iron and steel production. In continuous casting process, in order to improve the control precision of mould level under steady-state working condition, and to suppress large fluctuation under non-steady-state working condition, a fuzzy PID controller is designed based on working condition identification. First, a mechanism model of mould level is established. After analyzing the characteristics of the model, the continuous casting process is divided into different working conditions. Then, fuzzy rules are designed to regulate the parameters of PID. Finally, results in industrial site show both of the control precision of mould level under steady-state working condition and the anti-interference ability under non-steady-state working condition are improved, indicating that the proposed method is effective.
Smart Home system is the use of home life associated with hardware and related application technology, the introduction of home appliance automation, remote control, intelligent processing technology in a traditional ...
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Smart Home system is the use of home life associated with hardware and related application technology, the introduction of home appliance automation, remote control, intelligent processing technology in a traditional home environment, to design a provide users with comprehensive information exchange capabilities, in order to enhanced home life safety, comfort and convenience of home systems. At present, there are problems such as complicated wiring, single service, and high price in this field. In response to these problems, this paper designs a smart home system based on Zigbee and WIFI. The system consists of a terminal node, a gateway node and a remote control terminal. The terminal node and the gateway node form a home internal network through Zigbee technology, and the remote control terminal accesses and controls the home internal network through WIFI.
Drilling rigs are key devices in tunnel projects, which dig holes on a rock face by drilling arms. The quality and efficiency of tunnel constructions are directly determined by the positioning accuracy of the holes an...
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Drilling rigs are key devices in tunnel projects, which dig holes on a rock face by drilling arms. The quality and efficiency of tunnel constructions are directly determined by the positioning accuracy of the holes and time for traversing all the holes. This paper provides a complete solution for trajectory planning with accuracy and efficiency. First, this paper analyzes the structure of a drilling arm, establishes a forward kinematic model of the drilling arm by Denavit-Hartenberg convention. Next,to solve the inverse kinematics problem of drilling arm, a particle swarm optimization with adaptive inertia weight is ***, an optimal drilling sequence is found based on Hopfield network. Thereafter, a quintic polynomial method has been adopted to calculate the trajectory of the drilling arm. Finally, results of simulations show that the solution satisfies the accuracy of positioning and calculates the optimal trajectory.
With the increase in drilling depth, the encountered formations become more complicated, and industrial controller for weight on bit has limited precision due to the uncertain and varying formations. In this paper, we...
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With the increase in drilling depth, the encountered formations become more complicated, and industrial controller for weight on bit has limited precision due to the uncertain and varying formations. In this paper, we design a scheme of control system for weight on bit to achieve higher control precision in complex geological drilling process. A double-loop control structure is introduced, which involves with two system models: a multi-degree-of-freedom lumped parameter drill string model and a finite element bit-rock interaction model. The effect of varying formations on weight on bit is analyzed, and a control strategy for control system is presented in this paper.
The kernel learning algorithm has been widely used to solve the generalization problem existing in reinforcement learning. However, when the state-action space of the sample is large, the computation and storage burde...
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The kernel learning algorithm has been widely used to solve the generalization problem existing in reinforcement learning. However, when the state-action space of the sample is large, the computation and storage burden in the kernel learning algorithm will increase. In such case, there will be long running time and the real-time performance of the control system cannot be guaranteed. Therefore, in order to enhance the computational speed, this paper proposes a parallel architecture based iterative segmentation optimal cyclic block kernel learning algorithm. The experimental results show that the proposed method can significantly improve the computational efficiency of the kernel learning algorithm, which has important engineering practice significance.
In this paper, aiming at the pesticide residue in water resources, considering the necessity of rapid detection on site,a method based on machine vision for pesticide residue detection is proposed. The method combines...
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In this paper, aiming at the pesticide residue in water resources, considering the necessity of rapid detection on site,a method based on machine vision for pesticide residue detection is proposed. The method combines machine vision and image processing technology to quickly extract the RGB three-component eigenvalues of the pesticide residue detection card. Each RGB channel has 256 brightness levels, which can overcome the shortcomings of low brightness level and indistinct image,and improve the accuracy of detection. The results show that the method is simple,fast and efficient, it is suitable for quickly extracting the characteristic values of pesticide residue detection cards.
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