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Design, analysis, and control of a cable-driven parallel platform with a pneumatic muscle active support

Published online by Cambridge University Press:  19 October 2015

Xingwei Zhao*
Affiliation:
Chair of Mechatronics and Machine Dynamics, Technical University of Berlin, 10587, Berlin, Germany
Bin Zi
Affiliation:
School of Mechanical and Automotive Engineering, Hefei University of Technology, 230009, Hefei, P. R. China. [email protected]
Lu Qian
Affiliation:
Institute of Automatic Control and Complex Systems, University of Duisburg-Essen, 47057, Duisburg, Germany. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]

Summary

The neck is an important part of the body that connects the head to the torso, supporting the weight and generating the movement of the head. In this paper, a cable-driven parallel platform with a pneumatic muscle active support (CPPPMS) is presented for imitating human necks, where cable actuators imitate neck muscles and a pneumatic muscle actuator imitates spinal muscles, respectively. Analyzing the stiffness of the mechanism is carried out based on screw theory, and this mechanism is optimized according to the stiffness characteristics. While taking the dynamics of the pneumatic muscle active support into consideration as well as the cable dynamics and the dynamics of the Up-platform, a dynamic modeling approach to the CPPPMS is established. In order to overcome the flexibility and uncertainties amid the dynamic model, a sliding mode controller is investigated for trajectory tracking, and the stability of the control system is verified by a Lyapunov function. Moreover, a PD controller is proposed for a comparative study. The results of the simulation indicate that the sliding mode controller is more effective than the PD controller for the CPPPMS, and the CPPPMS provides feasible performances for operations under the sliding mode control.

Type
Articles
Copyright
Copyright © Cambridge University Press 2015 

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References

1. Kiapour, A., Kiapour, A. M., Kaul, V., Quatman, C. E., Wordeman, S. C., Hewett, T. E. and Goel, V. K., “Finite element model of the knee for investigation of injury mechanisms: Development and validation,” J. Biomech. Eng. 136 (1), 011002.1-011002.14 (2014).Google Scholar
2. Choi, K. W. and Schmitz, A. M., “Co-simulation of neuromuscular dynamics and knee mechanics during human walking,” J. Biomech. Eng. 136 (1), 021033.1-021033.8 (2014).Google Scholar
3. White, A. A. and Panjabi, M. M., Clinical Biomechanics of the Spine, (JB Lippincott, Philadelphian, 1990), vol. 2, pp. 108112.Google Scholar
4. Sakagami, Y., Watanabe, R., Aoyama, C., Matsunaga, S., Higaki, N. and Fujimura, K., “The Intelligent ASIMO: System Overview and Integration,” IEEE/RSJ International Conference on, Intelligent Robots and Systems, EPFL, Lausanne, Switzerland (2002), vol. 3, pp. 2478–2483.Google Scholar
5. Kaneko, K., Harada, K., Kanehiro, F., Miyamori, G. and Akachi, K., “Humanoid Robot Hrp-3,” IEEE/RSJ International Conference on, Intelligent Robots and Systems IROS 2008, Nice, France (2008) pp. 2471–2478.Google Scholar
6. Huang, Q., Peng, Z., Zhang, W., Zhang, L. and Li, K., “Design of Humanoid Complicated Dynamic Motion based on Human Motion Capture,” IEEE/RSJ International Conference on, Intelligent Robots and Systems, Alberta Canada (2005) pp. 3536–3541.Google Scholar
7. Lohmeier, S., Buschmann, T. and Ulbrich, H., “Humanoid Robot Lola,” IEEE International Conference on, Robotics and Automation ICRA'09, Kobe, Japan (2009) pp. 775–780.Google Scholar
8. Han, J., Zeng, S., Tham, K., Badgero, M. and Weng, J., “Dav: A Humanoid Robot Platform for Autonomous Mental Development,” Proceedings of the 2nd International Conference on Development and Learning, Cambridge, Massachusetts, USA (2002) pp. 73–81.Google Scholar
9. Guenter, F., Roos, L., Guignard, A. and Billard, A. G., “Design of a Biomimetic Upper Body for the Humanoid Robot Robota,” 5th IEEE-RAS International Conference on, Humanoid Robots, Tsukuba, Japan (2005) pp. 56–61.Google Scholar
10. Asfour, T., Azad, P., Vahrenkamp, N., Regenstein, K., Bierbaum, A., Welke, K., Schroder, J. and Dillmann, R., “Toward humanoid manipulation in human-centred environments,” Robot. Auton. Syst. 56 (1), 5465 (2008).Google Scholar
11. Carbone, G., Lim, H.-O., Takanishi, A. and Ceccarelli, M., “Stiffness analysis of biped humanoid robot WABIANRIV,” Mech. Mach. Theory 41 (1), 1740 (2006).Google Scholar
12. Holland, O. and Knight, R., “The Anthropomimetic Principle,” Proceedings of the AISB06 Symposium on Biologically Inspired Robotics, Bristol, UK (2006) pp. 1–8.Google Scholar
13. Jamone, L., Metta, G., Nori, F. and Sandini, G., “James: A Humanoid Robot Acting Over An Unstructured World,” 6th IEEE-RAS International Conference on Humanoid Robots, Genoa, Italy (2006) pp. 143–150.Google Scholar
14. Nori, F., Jamone, L., Sandini, G. and Metta, G., “Accurate Control of a Human-Like Tendon-Driven Neck,” 7th IEEE-RAS International Conference on Humanoid Robots, Pittsburgh, Pennsylvania (2007) pp. 371–378.Google Scholar
15. Gao, B., Song, H., Zhao, J., Guo, S., Sun, L. and Tang, Y., “Inverse kinematics and workspace analysis of a cable-driven parallel robot with a spring spine,” Mech. Mach. Theory 76 (1), 5669 (2014).Google Scholar
16. Lee, S. H. and Terzopoulos, D., “Heads up!: Biomechanical modeling and neuromuscular control of the neck,” ACM Trans. Graph. 25 (3), 11881198 (2006).Google Scholar
17. Liem, K., Kecskeméthy, A. and Merlet, J., “Hexaspine: A Parallel Platform for Physical Cervical Spine Simulation-Design and Interval-based Verification,” Proceedings of the 12th World Congress in Mechanism and Machine Science, BESANCON – FRANCE (2007) pp. 17–21.Google Scholar
18. Zi, B., Zhu, Z. C. and Du, J. L., 2011, “Analysis and control of the cable-supporting system including actuator dynamics,” Control Eng. Pract. 19 (5), 491501.Google Scholar
19. Zi, B., Duan, B. Y., Du, J. L. and Bao, H., “Dynamic modeling and active control of a cable-suspended parallel robot,” Mechatronics 18 (1), 112 (2008).Google Scholar
20. Bedoustani, Y. B., Taghirad, H. D. and Aref, M. M., “Dynamics Analysis of a Redundant Parallel Manipulator Driven by Elastic Cables,” 10th International Conference on, Control, Automation, Robotics and Vision ICARCV 2008, Hanoi, Vietnam (2008) pp. 536–542.Google Scholar
21. Hiller, M., Fang, S., Mielczarek, S., Verhoeven, R. and Franitza, D., “Design, analysis and realization of tendon-based parallel manipulators,” Mech. Mach. Theory 40 (4), 429445 (2005).Google Scholar
22. Zhao, X. and Zi, B., “Design and analysis of a pneumatic muscle driven parallel mechanism for imitating human pelvis,” Proc. Inst. Mech. Eng., Part C: Journal of Mechanical Engineering Science, 228 (4), 723741 (2014).Google Scholar
23. Chou, C. and Hannaford, B., “Measurement and modeling of mckibben pneumatic artificial muscles,” IEEE Trans. Robot. Autom. 12 (1), 90102 (1996).Google Scholar
24. Jamwal, P. K., Xie, S. Q., Hussain, S. and Parsons, J. G., “An adaptive wearable parallel robot for the treatment of ankle injuries,” IEEE/ASME Trans. Mechatronics 19 (1), 6475 (2012).Google Scholar
25. Zhu, X., Tao, G., Yao, B. and Cao, J., “Adaptive robust posture control of parallel manipulator driven by pneumatic muscles with redundancy,” IEEE/ASME Trans. Mechatronics 13 (4), 441450 (2008).Google Scholar
26. Xing, K., Wang, Y., Zhu, Q. and Zhou, H., “Modeling and control of mckibben artificial muscle enhanced with echo state networks,” Control Eng. Pract. 20 (5), 477488 (2012).Google Scholar
27. Khoa, L. D., Truong, D. Q. and Ahn, K. K., “Synchronization controller for a 3-R planar parallel pneumatic artificial muscle robot using modified ANFIS algorithm,” Mechatronics 23 (4), 462479 (2013).Google Scholar
28. Man, Z., Paplinski, A. P. and Wu, H. R., “A robust MIMO terminal sliding mode control scheme for rigid robotic manipulators,” IEEE Trans. Autom. Control 39 (12), 24642469 (1994).Google Scholar
29. Yong, F., Yu, X. and Man, Z., “Non-singular terminal sliding mode control of rigid manipulators,” Automatica 38 (12), 21592167 (2002).Google Scholar
30. Shen, X., “Nonlinear model-based control of pneumatic artificial muscle servo systems,” Control Eng. Pract. 18 (3), 311317 (2010).Google Scholar
31. Shi, G. L. and Shen, W., “Hybrid control of a parallel platform based on pneumatic artificial muscles combining sliding mode controller and adaptive fuzzy CMAC,” Control Eng. Pract. 21 (1), 7686 (2013).CrossRefGoogle Scholar
32. Ball, R. S., A Treatise on the Theory of Screws, Cambridge, UK (Cambridge University Press, 1990).Google Scholar
33. Liu, H., Huang, T. and Chetwynd, D. G., “A method to formulate a dimensionally homogeneous Jacobian of parallel manipulators,” IEEE Trans. Robot. 27 (1), 150156 (2011).Google Scholar
34. Ciblak, N. and Lipkin, H., “Asymmetric Cartesian Stiffness for the Modeling of Compliant Robotic Systems,” Proceedings of the 23rd Biennial ASME Mechanisms Conference, Minneapolis, MN (1994) pp. 197–204.Google Scholar
35. Ciblak, N. and Lipkin, H., “Synthesis of Cartesian Stiffness for Robotic Applications,” Proceedings of the IEEE International Conference on, Robotics and Automation, Detroit, Michigan (1999), vol. 3, pp. 2147–2152.Google Scholar
36. Gosselin, C. C. and Angeles, J. J., “A Global Performance Index for the Kinematic Optimization of Robotic Manipulators,” J. Mech. Des. 113 (3), 220226 (1991).Google Scholar
37. Chirikjian, G. S. and Kyatkin, A. B., Engineering Applications of Noncommutative Harmonic Analysis: With Emphasis on Rotation and Motion Groups, Boca Raton, Florida (CRC Press 2000).Google Scholar
38. Gosselin, C. M. and Grenier, M., “On the determination of the force distribution in overconstrained cable-driven parallel mechanisms,” Meccanica 46 (1), 315 (2011).Google Scholar
39. Ouyang, P. R., Zhang, W. J. and Wu, F. X., “Nonlinear PD Control for Trajectory Tracking with Consideration of the Design for Control Methodology,” Proceedings of the IEEE International Conference on, Robotics and Automation ICRA'02, Washington, D.C. (2002) pp. 4126–4131.Google Scholar
40. Wu, F. X., Zhang, W. J., Li, Q. and Ouyang, P. R., “Integrated design and PD control of high-speed closed-loop mechanisms,” J. Dyn. Syst. Meas. Control 124 (4), 522528 (2002).Google Scholar