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Journal articles on the topic 'Axis control'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

HASEGAWA, Koji, Keiichi NAKAMOTO, Tohru ISHIDA, and Yoshimi TAKEUCHI. "C2 Efficient 5-axis Control Drilling for a Large Number of Holes(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 113–16. http://dx.doi.org/10.1299/jsmelem.2009.5.113.

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2

UMEHARA, Takeshi, Koji TERAMOTO, Tohru ISHIDA, and Yoshimi TAKEUCHI. "Tool Posture Determination for 5-axis Control Machining by Area Division Method(Multi-axis control machining and measurement)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.1 (2005): 97–102. http://dx.doi.org/10.1299/jsmelem.2005.1.97.

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3

HIKICHI, Tatsuya, Keiichi NAKAMOTO, Tohru ISHIDA, and Yoshimi TAKEUCHI. "C1 Tool Path Generation for 5-Axis Control Machining Considering the Quality of Machined Surface(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 107–12. http://dx.doi.org/10.1299/jsmelem.2009.5.107.

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4

Tomizuka, Masayoshi, Jwu-Sheng Hu, Tsu-Chih Chiu, and Takuya Kamano. "Synchronization of Two Motion Control Axes Under Adaptive Feedforward Control." Journal of Dynamic Systems, Measurement, and Control 114, no. 2 (June 1, 1992): 196–203. http://dx.doi.org/10.1115/1.2896515.

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In this paper, motion synchronization of two d-c motors, or motion control axes, under adaptive feedforward control is considered. The adaptive feedforward control system for each axis consists of a proportional feedback controller, an adaptive disturbance compensator and an adaptive feedforward controller. If the two adaptive systems are left uncoupled, a disturbance input applied to one of the two axes will cause a motion error in the disturbed axis only, and the error becomes the synchronization error. To achieve a better synchronization, a coupling controller, which responds to the synchronization error, i.e., the difference between the two motion errors, is introduced. In this case, when a disturbance input is applied to one axis, the motion errors appear in the undisturbed axis as well as in the disturbed axis. The motion error in the undisturbed axis is introduced by the coupling controller and the adaptive feedforward controller. The adaptive synchronization problem is formulated and analyzed in the continuous time domain first, and then in the discrete time domain. Stability conditions are obtained. Effectiveness of the adaptive synchronization controller is demonstrated by simulation.

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5

TAKESHIMA, Hideyuki, and Yukitoshi IHARA. "C4 Finished Test Piece Example for Five-axis Machining Centers(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 123–26. http://dx.doi.org/10.1299/jsmelem.2009.5.123.

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6

KITAMURA, Akihiro, Yoshimi TAKEUCHI, and Takashi SAITOU. "Development of Die Mold Processing Machine with Multi-Spindles and Axes(Multi-axis control machining and measurement)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.1 (2005): 91–96. http://dx.doi.org/10.1299/jsmelem.2005.1.91.

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7

SATO, Ryuta, Yuya YOKOBORI, and Masaomi TSUTSUMI. "Synchronous Accuracy of Translational and Rotary Axes in 5-axis Machining Centers(Precision positioning and control technology)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.3 (2005): 993–98. http://dx.doi.org/10.1299/jsmelem.2005.3.993.

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8

KANEKO, Jun'ichi, and Kenichiro HORIO. "Fast Evaluation Method of Tool Posture for 5-Axis Control Machining Using New Functions of Graphics Hardware(Multi-axis control machining and measurement)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.1 (2005): 103–8. http://dx.doi.org/10.1299/jsmelem.2005.1.103.

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9

Jezernik, K., and V. Volčanjk. "Single Axis Robot Control." IFAC Proceedings Volumes 27, no. 4 (June 1994): 183–87. http://dx.doi.org/10.1016/s1474-6670(17)46020-4.

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10

YAMAMOTO, Toru, Takao HASEBE, and Masaomi TSUTSUMI. "C5 Development of Groove-Matrix Machining Method for Evaluating 5-Axis Machining Centers(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 127–32. http://dx.doi.org/10.1299/jsmelem.2009.5.127.

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11

Fracker, Martin L., and Christopher D. Wickens. "Resources, Confusions, and Compatibility in Dual Axis Tracking: Displays, Controls, and Dynamics." Proceedings of the Human Factors Society Annual Meeting 31, no. 11 (September 1987): 1211–15. http://dx.doi.org/10.1177/154193128703101107.

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Dual axis compensatory tracking was investigated as a function of whether error displays were integrated or separated, whether axis controls were integrated into one stick or remained separate, and whether the control dynamics on the two axes were the same or different. Tracking error increased and control activity decreased as a function of the summed difficulty of the two control dynamics. Integrated displays and integrated controls both led to increased confusions between tracking axes although error was unaffected. Importantly, performance was also affected by whether the integrality of displays matched that of controls. These results suggest that dual axis tracking is subject to independent effects of resource competition, confusions, and Wickens' (1986b) compatibility of proximity principle.

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12

Sato, Ryuta, and Masaomi Tsutsumi. "High Performance Motion Control of Rotary Table for 5-Axis Machining Centers." International Journal of Automation Technology 1, no. 2 (November 5, 2007): 113–19. http://dx.doi.org/10.20965/ijat.2007.p0113.

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We discuss motion control techniques of rotary tables for 5-axis machining centers. Three translational axes and two rotary ones are controlled simultaneously in the machining of complex shapes such as impellers. A tilting rotary table powered by a worm gear is generally used as the rotary axes for 5-axis machining centers, and various causes of inaccuracy exist in the rotary axes. In this study, we clarified three causes of inaccuracy exists in the rotary axis: rotational fluctuation in the worm gear, backlash, and measurement delay of rotary encoder for feedback. Motor torque saturation of the rotary axis also causes a problem when rotational velocity is changed rapidly. Based upon investigated results, we propose compensators for improving synchronous accuracy. We avoid torque saturation in the rotary axis through acceleration-deceleration design. To verify the effectiveness of the proposed compensators, we applied them to an experimental set-up including a rotary axis. As the results of experiments, it is clarified that the proposed compensators improve the synchronous accuracy of translational and rotary axes.

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13

Sudo, Masako. "Advanced Control Technologies for 5-Axis Machining." International Journal of Automation Technology 1, no. 2 (November 5, 2007): 108–12. http://dx.doi.org/10.20965/ijat.2007.p0108.

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Demand for 5-axis machine tools has grown rapidly with the appearance of high-performance machines and growing requirements for high-efficiency to enhance competitiveness. To meet market needs, FANUC provides innovative CNCs, including the FS30i-A and FS31i-A5, that control up to 24 axes simultaneously with maximum paths of 10 enabling high-speed and high-precision multiple-axis and path control. FANUC's wide-ranging functions developed for powerful 5-axis machining include tool center point control and tilted working plane command, which enable high-precision complex shape machining minimizing changeover. Nano smoothing, interpolation for generating smooth curves on a nanometer scale, enables high-quality workpiece machining. 3D interference checking enhances the safety of machines whose motion has become increasingly complex. Operability has also been improved to facilitate programming and simulation for 5-axis machining. This report presents the latest control technologies maximizing 5-axis machine tool performance.

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14

D’Elia, Giacomo, and Emiliano Mucchi. "Comparison of single-input single-output and multi-input multi-output control strategies for performing sequential single-axis random vibration control test." Journal of Vibration and Control 26, no. 21-22 (February 24, 2020): 1988–2000. http://dx.doi.org/10.1177/1077546320909975.

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This study investigates the use of single-input single-output and multi-input multi-output control strategies for performing single-axis vibration control tests. In particular, the work addresses the problem of high-level cross-axis responses during those tests. To compare the two control strategies, the study presents a test campaign carried out on an automotive component by exploiting two different test facilities: a single-axis shaker and a three-degree-of-freedom shaker table. The analysis points out the limitations of the single-input single-output control strategy. The coupling between the excitation system and the test specimen causes cross-axis excitations that compromise the test validity. In some cases, the cross-axis vibration level even exceeds the acceptable threshold of 14 dB. The multi-input multi-output control strategy instead, besides the feedback control of the main axis, allows the simultaneous vibration control along the two cross axes, thus, improving the quality of the single-axis test. Moreover, the work provides a detailed study followed by practical examples on how to better exploit the evident potential of the multi-input multi-output control strategy for definitely avoiding cross-axis vibration control problems.

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15

Takeuchi, Yoshimi. "Multi-Axis Control Ultraprecision Micromilling." Key Engineering Materials 447-448 (September 2010): 801–5. http://dx.doi.org/10.4028/www.scientific.net/kem.447-448.801.

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In recent years, ultraprecision micromachining technology draws wide attention. In particular, multi-axis control ultraprecision machine tools are playing an important role in producing complicated microparts made of a variety of materials. In addition, CAM software is also an essential element to control these machine tools. The paper deals not only with the current state of multi-axis control ultraprecision machine tools but also with the manufacture of two workpieces consisting of complicated shapes by means of micromilling.

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16

Dunlop, G. R. "Multi-axis step motor control." Transactions of the Institute of Measurement and Control 8, no. 2 (April 1986): 85–90. http://dx.doi.org/10.1177/014233128600800205.

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17

YAMADA, Makoto, Tsukasa KONDO, Fumiki TANAKA, and Takeshi KISHINAMI. "3+2 Axis Control Machining on 5-axis Machine Tools." Proceedings of The Manufacturing & Machine Tool Conference 2004.5 (2004): 157–58. http://dx.doi.org/10.1299/jsmemmt.2004.5.157.

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18

Chiu, George T. C., and Masayoshi Tomizuka. "Coordinated Position Control of Multi-Axis Mechanical Systems." Journal of Dynamic Systems, Measurement, and Control 120, no. 3 (September 1, 1998): 389–93. http://dx.doi.org/10.1115/1.2805413.

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Position coordination of multi-axis mechanical systems is studied. Under the assumption that the coordination objective can be represented by smooth functions of the positions of the multiple axes control systems, a necessary coupling effect can be introduced to each axis by the proper choice of a Lyapunov-like function. The resulting, control law requires the knowledge of the desired trajectories and their time derivatives as well as actual position and velocity information. Implementation of the proposed control algorithm on a CNC feed drive system shows significant improvement in dimensional accuracy during high speed contouring.

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19

KANEKO, Jun'ichi, and Kenichiro HORIO. "C9 Tool posture planning method for 5-axis control machining with an idea of spatial temporal representation based on machine tool coordinate system(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 149–54. http://dx.doi.org/10.1299/jsmelem.2009.5.149.

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20

Lee, Jung-Hyung, Donghoon Kim, Jichul Kim, and Hwa-Suk Oh. "Shorter Path Design and Control for an Underactuated Satellite." International Journal of Aerospace Engineering 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/8536732.

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In the event of a control failure on an axis of a spacecraft, a target attitude can be achieved by several sequential rotations around the remaining control axes. For a spacecraft actuating with wheels, the form of each submaneuver should be a pure single axis rotation since the failed axis should not be perturbed. The rotation path length in sequential submaneuvers, however, increases extremely but is short under normal conditions. In this work, it is shown that the path length is reduced dramatically by finding a proper number of sequential submaneuvers, especially for the target attitude rotation around the failed axis. A numerical optimization is suggested to obtain the shortest path length and the relevant number of maneuvers. Optimal solutions using the sequential rotation approach are confirmed by numerical simulations.

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21

Hu, Zhu Bing, and Yan Hua Wang. "Control Research of Three-Axis Turntable Based on Neural Network Inverse System." Applied Mechanics and Materials 347-350 (August 2013): 121–24. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.121.

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For the nonlinear coupling characteristics between three axes of the three-axis turntable, a method which combines the inverse system method and Neural Network (NN) has been put forward. This method realizes linearization and decoupling of three-axis turntable and solves the defect of difficult to realize precise decoupling with inverse system method when the model of three-axis turntable is inaccurate. Simulation results show the feasibility of the method and also good robustness and resistance.

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22

Hansen, Clint, Nasser Rezzoug, Philippe Gorce, and Brice Isableu. "Differences in the Control of Unconstrained Three-Dimensional Arm Motions of the Dominant and the Nondominant Arm." Journal of Applied Biomechanics 32, no. 3 (June 2016): 311–15. http://dx.doi.org/10.1123/jab.2015-0286.

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For the dominant limb, a velocity-dependent change in rotational axes during the kinesthetic control of unconstrained 3D arm rotations was reported, and thus the question arises if this can be reproduced for the nondominant arm. The rotation axes considered are the axes of minimum inertia (e3), the shoulder–center of mass axis (SH-CM), and the shoulder–elbow axis (SH-EL). The objective of this study was to examine whether the minimum inertia axis would constrain internal–external rotations of the shoulder at fast velocity. Participants performed cyclic rotations of their arms in 2 sensory conditions and at 2 velocities. The elbow configurations were either set to 90° or 140° to yield a constant separation between e3, SH-CM, and SH-EL. Our results showed that the limb’s rotational axis coincide with the SH-EL axis across velocity conditions, although higher variability was seen at higher velocity. This was true for both the dominant and the nondominant arm. Together, the results showed that cognitive instruction prevented a velocity-dependent rotation axis change toward e3 and/or SH-CM, as proposed in the minimum inertia principle.

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23

She, Chen Hua, and Tsung Hua Yang. "Design of a Cutting Point Control Algorithm for Five-Axis Machining." Applied Mechanics and Materials 249-250 (December 2012): 702–6. http://dx.doi.org/10.4028/www.scientific.net/amm.249-250.702.

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Five-axis machine tool with two additional rotary axes has been widely used in defense, aerospace and the consumer industries, and is an important process of precision manufacturing. Traditional five-axis program depends on the machine tool’s configuration and machining setting. This leads to inconvenience of reprogramming five-axis NC code for the end users. This paper proposes a cutting point control algorithm for five-axis machining. Although the commercial advanced controllers provide this function, they are very expensive and restricted to export. The developed algorithm can be embedded to the PC-based controller so that the specific cutter location data can be transformed and employed easily for different cutting tools. Verification using VERICUT solid cutting simulation software demonstrated the correctness of the generated cutter location data.

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24

Barendswaard, Sarah, Daan Marinus Pool, Marinus M. Van Paassen, and Max Mulder. "Dual-Axis Manual Control: Performance Degradation, Axis Asymmetry, Crossfeed, and Intermittency." IEEE Transactions on Human-Machine Systems 49, no. 2 (April 2019): 113–25. http://dx.doi.org/10.1109/thms.2019.2890856.

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25

Wang, Ji Dai, Cun Xian Liang, and Ai Qin Sun. "A Multi-Axis Synchronization Control Approach Based on Adjacent Cross-Coupling Strategy." Applied Mechanics and Materials 644-650 (September 2014): 510–15. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.510.

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The high precision synchronized multi-axis control has become one of the key issues in modern manufacturing industry. As synchronized multi-axis control systems are nonlinear, time-variable and easily affected by disturbances, it is difficult to determine reasonable coupling control law and large amount of on-line calculation just through the existing synchronous control strategies for multi-axis system. In this paper the development status of multi-axis control synchronization control strategy is analyzed and the synchronization control algorithm is proposed based on the adjacent coupling error. The parameters of cross-coupled control are set on the basis of BP neural network control theory, which can not only reduce the tracking error, but also eliminate the synchronization error between adjacent axes. The synchronization performance of this approach is good with simple configuration. With this approach, the synchronization performance is good with simple configuration. Simulation results of the multi-axis synchronous system show that this method can effectively obtain the synchronization with a quick convergence. In the end, the multi-axis cross-coupled control approach based on BP neural networks is applied to a three-axis synchronization control system and its effectiveness is discussed.

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26

Baba, Shinnosuke, Keiichi Nakamoto, and Yoshimi Takeuchi. "Multi-Axis Control Ultraprecision Machining Based on Tool Setting Errors Compensation." International Journal of Automation Technology 10, no. 1 (January 4, 2016): 114–20. http://dx.doi.org/10.20965/ijat.2016.p0114.

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Initial position errors generated while setting cutting tools can deteriorate machining accuracy. However, because of the manual setting process, it is difficult to prevent the tool setting errors, which can increase in accordance with the number of the control axes. These errors make it difficult to locate the tool accurately at the correct position in multi-axis control machining. Therefore, this study aims to achieve multi-axis control ultraprecision machining based on tool setting errors compensation. From the conducted experiments, it is found that the proposed method is effective for compensating the tool setting errors in multi-axis control ultraprecision machining.

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27

Niu, Weiguang, and Masayoshi Tomizuka. "A New Approach of Coordinated Motion Control Subjected to Actuator Saturation." Journal of Dynamic Systems, Measurement, and Control 123, no. 3 (July 22, 1999): 496–504. http://dx.doi.org/10.1115/1.1387247.

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In this paper, a new approach of motion coordination of two axes systems in the presence of actuator saturation is proposed. The proposed approach includes two parts: feedback controller and on-line trajectory planning. The feedback controller is designed using an anti-windup design to reduce the degradation in performance of each axis when saturation occurs. An on-line trajectory planning algorithm is also proposed to maintain the contouring accuracy during saturation periods. The desired outputs for X- and Y-axis are given as sequences of points. When the actuator of any axis is predicted to saturate, an appropriate number of points are inserted in the original sequence to slow down the motion. The effectiveness of the proposed approach is studied by simulation of a two-axis Cartesian positioning system.

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28

Chapman, I. T., I. Jenkins, R. V. Budny, J. P. Graves, S. D. Pinches, and S. Saarelma. "Sawtooth control using off-axis NBI." Plasma Physics and Controlled Fusion 50, no. 4 (February 27, 2008): 045006. http://dx.doi.org/10.1088/0741-3335/50/4/045006.

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29

Lam, Denise, Chris Manzie, and Malcolm C. Good. "Multi-axis model predictive contouring control." International Journal of Control 86, no. 8 (August 2013): 1410–24. http://dx.doi.org/10.1080/00207179.2013.770170.

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30

Pham Thuong Cat. "Robust adaptive axis control of manipulator." Robotics and Computer-Integrated Manufacturing 3, no. 3 (January 1987): 285–93. http://dx.doi.org/10.1016/0736-5845(87)90035-4.

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31

Muditha Dassanayake K. M., Masaomi TSUTSUMI, and Akinori SAITO. "A Strategy for Identifying Static Deviations in Universal Spindle Head Type Multi-axis Machining Centers(Multi-axis control machining and measurement)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.1 (2005): 121–26. http://dx.doi.org/10.1299/jsmelem.2005.1.121.

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32

Takeuchi, Yoshimi. "Special Issue on Multiaxis Control and Multitasking Machine Tools." International Journal of Automation Technology 1, no. 2 (November 5, 2007): 77. http://dx.doi.org/10.20965/ijat.2007.p0077.

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Machine tools using numerical control (NC) devices are typical mechatronics products and a powerful way to automate plant production. The introduction of multiaxis control and multitasking machine tools to workshops is growing to meet the requirements of highly efficient, precision machining of a variety of complex products and mold dies. The increase in the number of control axes and multitasking capability in one chucking process enable machine tools to manufacture complex products efficiently and accurately. Given the strong attention and interest multiaxis control and multitasking machine tools are attracting, it is about time to introduce the current state of the art of these tools and their practical and applicable technologies, especially in Japan. This special issue covers the development of 5-axis control machining centers, machine tools having multispindle heads with 5-axis control, 5-axis control CAMs, accuracy evaluation for 5-axis control machine tools, and more. We thank the authors for their interesting papers to this special issue, and are certain that both general readers and specialists will find the information they provide both interesting and informative.

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33

MIYAMA, Naoki, Tomoyuki SAIKI, Chengri CUI, and Masaomi TSUTSUMI. "C3 Generalization of Identification Method of Geometric Deviations for Five-axis Machining Centers with a Tilting-rotary Table(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 117–22. http://dx.doi.org/10.1299/jsmelem.2009.5.117.

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34

IZAWA, Yuya, Koichi MORISHIGE, Feliciano H. JAPITANA, Shugo YASUDA, and Yoshimi TAKEUCHI. "Efficient Machining of Character Line Using Five-Axis and Six-Axis Control." Proceedings of the JSME annual meeting 2002.5 (2002): 347–48. http://dx.doi.org/10.1299/jsmemecjo.2002.5.0_347.

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35

Kawaguchi, Yasuhiro, Keiichi Nakamoto, Toru Ishida, and Yoshimi Takeuchi. "C8 Artistic Machining by Means of Multi-tasking Machine(Multi-axis control machining)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2009.5 (2009): 145–48. http://dx.doi.org/10.1299/jsmelem.2009.5.145.

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36

Yalçın, Barış Can, and Haluk Erol. "Semiactive Vibration Control for Horizontal Axis Washing Machine." Shock and Vibration 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/692570.

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A semiactive vibration control method is developed to cope with the dynamic stability problem of a horizontal axis washing machine. This method is based on adjusting the maximum force values produced by the semiactive suspension elements considering a washing machine’s vibration data (three axis angular position and three axis angular acceleration values in time). Before actuation signals are received by the step motors of the friction dampers, vibration data are evaluated, and then, the step motors start to narrow or expand the radius of bracelets located on the dampers. This changes the damping properties of the damper in the suspension system, and thus, the semiactive suspension system absorbs unwanted vibrations and contributes to the dynamic stability of the washing machine. To evaluate the vibration data, the angular position and angular acceleration values in three axes are defined in a function, and the maximum forces produced by semiactive suspension elements are calculated according to the gradient of this function. The relation between the dynamic stability and the walking stability is also investigated. A motion (gyroscope and accelerometer) sensor is installed on the top-front panel of the washing machine because a mathematical model of a horizontal axis washing machine suggests that the walking behavior starts around this location under some assumptions, and therefore, calculating the vibrations occurring there is crucial. Semiactive damping elements are located under the left and right sides of the tub. The proposed method is tested during the spinning cycle of washing machine operation, increasing gradually from 200 rpm to 900 rpm, which produces the most challenging vibration patterns for dynamic stability. Moreover, the sound power levels produced by the washing machine are measured to evaluate the noise performance of the washing machine while the semiactive suspension system is controlled. The effectiveness of the proposed control method is shown through experimental results.

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37

Kuo, L.-Y., and J.-Y. Yen. "A genetic algorithm-based parameter-tuning algorithm for multi-dimensional motion control of a computer numerical control machine tool." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 216, no. 3 (March 1, 2002): 429–38. http://dx.doi.org/10.1243/0954405021519915.

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This paper addresses an automatic parameter-tuning algorithm for the multi-axis motion control of a computer numerical control (CNC) machine centre. The traditional approach to tune the control parameters in the multi-axis machines is to tune each axis independently. Some high-end-precision machines offer cross-axis motion parameters for impedance compensation but this is usually not satisfactory for practical purpose. Because each axis on the machine centre contributes to more than one working plane, obtaining the optimal performance for motions involving more than one plane often results in axis coupling. This paper introduces a systematic method to tune the servo parameters for multi-axis motion control. The tuning algorithm is based upon an intelligent genetic algorithm (GA) and the parameters are tuned for each work plane. The method optimized the multi-axis motion performance. A modified GA is also proposed to solve the convergence problem induced by a large number of parameters in multi-axis motion tuning.

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38

Wang, Bin Wu, Yan Hua Sun, and Wen Zhang. "The Control Simulation Analysis of MATLAB-Based High-Precision Numerical Control Welding Positioner." Advanced Materials Research 466-467 (February 2012): 1363–67. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.1363.

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Based on electromechanical system dynamics model of 3-axis NC positioned, together with the general nonlinear decoupling control theory, the decoupling control method of NC 3-axis positioned is proposed in this paper. In order to control each axis and the simulation of the decoupling control, the Simulink platform of MATLAB soft is used to build a electromechanical system simulation model for NC positioned. The results show that the proposed nonlinear decoupling feedback control method is effective and applicable.

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39

Aravindh Kumar, SM, and Ethirajan Rathakrishnan. "Elliptic jet control with triangular tab." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 8 (June 10, 2016): 1460–77. http://dx.doi.org/10.1177/0954410016652921.

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Elliptic jet mixing influenced by triangular tabs is demonstrated in this work. Mixing modification of a Mach 2 jet from a convergent-divergent elliptic nozzle of aspect ratio 2, in the presence of two triangular tabs along the major and minor axis at the nozzle exit, at different levels of nozzle expansion has been studied. The results show that the mixing caused by tabs along the minor axis is impressive compared to the uncontrolled jet at all the pressure ratios. But for tabs along the major axis, mixing enhancement is significant only for nozzle pressure ratios above 5. Tabs along the minor axis cause better mixing than tabs along the major axis. The iso-pitot pressure contours reveal that the tabs along the minor axis enhance the mixing by bifurcating the jet. Shadowgraphs show that the tabs render the waves in the jet weaker. The present study demonstrates the superior mixing promotion caused by triangular tab than rectangular tab, studied by Aravindh Kumar and Rathakrishnan (2015).

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40

Xia, Jin Song, and Guang Hui Yang. "A Method for Generating Customizable Coordinate Axes in AxSceneControl." Applied Mechanics and Materials 373-375 (August 2013): 433–36. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.433.

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Coordinate axes have been used extensively in three-dimensional (3D) GIS processing to help visualize the location of points directly. Meanwhile, AxSceneControl is a visual control provided by ESRI®ArcGIS®Engine, which is suited to generating perspective scenes that allow user to navigate and interact with 3D feature and raster data. However, there is no direct solution given by ArcGIS Engine to set Coordinate axes in 3D scenes. In this paper, we proposed and implemented an approach to generate and customize coordinate axis in AxSceneControl. By this method, up to five coordinate axes, named as x axis, y axis, z axis, top axis and right axis, can be drawn based on the layer that is loaded to the AxSceneControl. Furthermore, users can modify the properties of coordinate axes such as changing the style of degree scale, determining which axis will be shown and resizing the degree density to achieve simple coordinate axis.

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Wang, Sanxiu, Yue Chen, and Guoan Zhang. "Adaptive fuzzy PID cross coupled control for multi-axis motion system based on sliding mode disturbance observation." Science Progress 104, no. 2 (April 2021): 003685042110118. http://dx.doi.org/10.1177/00368504211011847.

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Multi-axis motion system is widely applied in commercial industrial machines such as precision CNC machine tools, Robot manipulator and laser cutting machines, etc. Contour accuracy plays a major role for the multi-axis servo motion system. The contour machining accuracy is related to the synthesis of single-axis position accuracy and multi-axis linkage accuracy. Only improving the single-axis tracking performance cannot effectively guarantee the machining accuracy of multi-axis system. The primary objective of this study was to design a contour control method to improve single-axis tracking accuracy and multi-axis contour accuracy. A control strategy that combines a sliding mode tracking controller, a disturbance observer and an adaptive fuzzy PID cross coupled controller is proposed. Sliding mode control is simple and has strong robustness to parameter changes and disturbance, which is especially suitable for control of such as non-linear multi-axis motion system. Besides, disturbance is inevitable in practical application, which degrades the motion accuracy. In order to eliminate the influence of external disturbance and uncertainty, disturbance observer is adopted to accurately estimate external disturbance and reduce the chattering phenomenon of sliding mode control, then improve the single-axis tracking accuracy. In order to further consider the coordination between different motion axes and improve the contour accuracy, the PID cross coupled control is used. Owing to conventional PID control cannot satisfy the multi-axis servo motion system with nonlinearity and uncertainty, an adaptive fuzzy method with on-line real-time PID parameters adjustment is proposed. The three-axis motion platform driven by PMLSM is used as the control object, to analysis the influence of disturbance observer on sliding mode control signal and analysis adaptive fuzzy PID cross coupled control performance respectively. The disturbance observer is used to observe the disturbance signal and estimate the disturbance well. The chattering of the sliding mode control signal is obviously improved. Next, compared with the conventional PID-CCC control, adaptive fuzzy PID- CCC control can significantly reduce the tracking error, the contour accuracy is also obviously improved. The disturbance observer can effectively eliminate the influence of external disturbance, reduce the chattering of sliding mode control, and ensure the single-axis accurate tracking. The self-adaptive fuzzy PID cross coupled controller can eliminate the influence of the dynamic characteristics mismatching and parameter difference of each axis, and improve contour accuracy. The simulation results clearly demonstrate the effectiveness of the proposed control method.

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Zhao, Liang, Jing Chuan Dong, Zhi Feng Qiao, Yan Yu Ding, and Zhi Yuan Tang. "An Algorithm for Space Tool Compensation Used in Five-Axis Numerical Control System." Applied Mechanics and Materials 141 (November 2011): 186–90. http://dx.doi.org/10.4028/www.scientific.net/amm.141.186.

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This paper presents a new space cutter compensation algorithm used in five-axis CNC machines. Five-axis CNC machines are composed of three linear axes and two rotational axes, owing to its unique structure and function, especially it is adapted to free surface machining, and is used in mold, aviation and ship manufacture widely. This paper analyzes cutter’s feed path, creates a local coordinate system in the CC point by using transformation equation between CL point and CC point. In this local coordinate system cutter compensation is built, new CL point and new cutter angle is calculated. Through coordinate system transformation matrix, determine cutter absolute coordinate.

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Astarloa, Armando, Jesús Lázaro, Unai Bidarte, Jaime Jiménez, and Aitzol Zuloaga. "FPGA technology for multi-axis control systems." Mechatronics 19, no. 2 (March 2009): 258–68. http://dx.doi.org/10.1016/j.mechatronics.2008.09.001.

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Zhang, Zhipeng, and Chia-Hsiang Menq. "Six-Axis Magnetic Levitation and Motion Control." IEEE Transactions on Robotics 23, no. 2 (April 2007): 196–205. http://dx.doi.org/10.1109/tro.2007.892232.

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Goodyear, S. W., R. G. Humphreys, J. S. Satchell, N. G. Chew, M. J. Wooliscroft, and K. Lander. "Control and reproducibility of c-axis microbridges." IEEE Transactions on Appiled Superconductivity 7, no. 2 (June 1997): 2734–37. http://dx.doi.org/10.1109/77.621803.

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Barbi, Joseph, Drew Pardoll, and Fan Pan. "Metabolic control of the Treg/Th17 axis." Immunological Reviews 252, no. 1 (February 13, 2013): 52–77. http://dx.doi.org/10.1111/imr.12029.

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Shalabi, S. El, M. Ebrahimi, B. Mason, R. Whalley, and A. A. Ameer. "Hydraulic axis actuation control for precision motion." International Journal of Computer Aided Engineering and Technology 1, no. 2 (2009): 173. http://dx.doi.org/10.1504/ijcaet.2009.022785.

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TAKEUCHI, Yoshimi, Geqi YE, and Manabu ISHIGURO. "Squared Corner Shaping by 6-Axis Control." Journal of the Japan Society for Precision Engineering 62, no. 12 (1996): 1762–66. http://dx.doi.org/10.2493/jjspe.62.1762.

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HISAKI, Tatsuya, and Yoshimi TAKEUCHI. "6-Axis Control Finishing for Character Line." Journal of the Japan Society for Precision Engineering 62, no. 2 (1996): 230–35. http://dx.doi.org/10.2493/jjspe.62.230.

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Stein, David S., and Leslie M. Stevens. "Maternal control of theDrosophiladorsal-ventral body axis." Wiley Interdisciplinary Reviews: Developmental Biology 3, no. 5 (May 29, 2014): 301–30. http://dx.doi.org/10.1002/wdev.138.

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