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Dynamic feedforward control of spatial cable-driven hyper-redundant manipulators for on-orbit servicing

Published online by Cambridge University Press:  29 August 2018

Zonggao Mu ,
Tianliang Liu ,
Wenfu Xu ,
Yunjiang Lou  and
Bin Liang
Zonggao Mu
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
Tianliang Liu
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
Wenfu Xu*
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
Yunjiang Lou
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China
Bin Liang
Affiliation:
Department of Automation, School of Information Science and Technology, Tsinghua University, Beijing 100084, China
*
*Corresponding author. E-mail: wfxu@hit.edu.cn
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Summary

The hyper-redundant manipulators are suitable for working in the constrained on-orbit servicing environment due to the extreme flexibility. However, its modelling and control are very challenging due to the characteristics of non-linearity and strong coupling. In this paper, considering the multi-level mapping among the motors, cables, joints, and end-effector, a proportional derivative (PD) with dynamic feedforward compensation control system is designed. The corresponding control system is divided into five parts: controller, planner, actuator, manipulator, and sensor. The actual control torque consisting of the desired feedforward torque and the feedback torque is generated by the controller. In order to improve the tracking accuracy and maintain rapid response, the torque, which is calculated by the dynamics model of the traditional joint-driven manipulator, is regarded as the desired feedforward torque. The parameters of interest are the angle and velocity of the universal joint and motors. The planner plans and converts the desired parameters of the universal joint to corresponding motors. Combining with the feedback angles and velocities signals of the corresponding motors, the feedback torque can be calculated by the PD control module. Finally, typical cases of six universal joints (12DOFs) manipulators are simulated and experimented. The results demonstrate that the method is very efficient for controlling spatial cable-driven hyper-redundant manipulators.

Keywords

Hyper-redundant manipulatorCable drivenDynamic feedforwardPD controlOn-orbit servicing

Information

Type
Articles
Information
Robotica , Volume 37 , Issue 1 , January 2019 , pp. 18 - 38
Copyright
Copyright © Cambridge University Press 2018 

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References

1. Flores-Abad, A., Ma, O., Pham, K. and Ulrich, S., “A review of space robotics technologies for on-orbit servicing,” Prog. Aerosp. Sci. 68, 1–26 (2014).Google Scholar
2. Huang, P., Cai, J., Meng, Z., Hu, Z. and Wang, D., “Novel method of monocular real-time feature point tracking for tethered space robots,” J. Aerosp. Eng. 27 (6), 4014039 (2013).Google Scholar
3. Meng, Z. and Huang, P., “Universal dynamic model of the tethered space robot,” J. Aerosp. Eng. 29 (1), 4015026 (2016).Google Scholar
4. Huang, P., Chen, L., Zhang, B., Chen, H., Meng, Z. and Liu, Z., “Autonomous rendezvous and docking with nonfull field of view for tethered space robot,” Int. J. Aerosp. Eng. 2017 (11), 1–11 (2017).Google Scholar
5. Montazeri, A., West, C., Monk, S. D. and Taylor, C. J., “Dynamic modelling and parameter estimation of a hydraulic robot manipulator using a multi-objective genetic algorithm,” Int. J. Control 90 (4), 661–683 (2017).Google Scholar
6. Nanos, K. and Papadopoulos, E. G., “On the dynamics and control of flexible joint space manipulators,” Control Eng. Pract. 45, 230–243 (2015).Google Scholar
7. Paraskevas, I. S. and Papadopoulos, E. G., “Parametric sensitivity and control of on-orbit manipulators during impacts using the centre of percussion concept,” Control. Eng. Pract. 47, 48–59 (2016).Google Scholar
8. Xu, W., Yan, L., Mu, Z. and Wang, Z., “Dual arm-angle parameterisation and its applications for analytical inverse kinematics of redundant manipulators,” Robotica 34, 2669–2688 (2016).Google Scholar
9. Xu, W., Mu, Z., Liu, T. and Liang, B., “A modified modal method for solving the mission-oriented inverse kinematics of hyper-redundant space manipulators for on-orbit servicing,” Acta Astronaut. 139, 54–66 (2017).Google Scholar
10. Spanos, P. D., Berka, R. B. and Tratskas, P., “Multisegment large space robot: Concept and design,” J. Aerosp. Eng. 13 (4), 123–132 (2000).Google Scholar
11. Liu, J., Wang, Y., Li, B. and Ma, S., “Neural Network Based Kinematic Control of the Hyper-Redundant Snake-Like Manipulator,” Proceedings of International Symposium on Neural Networks: Advances in Neural Networks (Springer-Verlag, Berlin Heidelberg, 2007) pp. 767–775.Google Scholar
12. Tang, Z. L., Ge, S. S., Tee, K. P. and He, W., “Adaptive neural control for an uncertain robotic manipulator with joint space constraints,” Int. J. Control 89 (7), 1–33 (2015).Google Scholar
13. Panwar, V., “Wavelet neural network-based H∞ trajectory tracking for robot manipulators using fast terminal sliding mode control,” Robotica 1, 1–16 (2016).Google Scholar
14. Jones, B. A. and Walker, I. D., “Practical kinematics for real-time implementation of continuum robots,” IEEE Trans. Robot. 22 (6), 1087–1099 (2006).Google Scholar
15. Ivanescu, M., Bizdoaca, N., Florescu, M. and Popescu, N., “Frequency Criteria for the Grasping Control of a Hyper-redundant Robot,” IEEE International Conference on Robotics and Automation (2010) pp. 3981–3988.Google Scholar
16. Yi, H., Min, S. A. and Hong, D. W., “Adaptive Fuzzy-PI control of redundant humanoid arm using full-body balance,” J. Intell. Fuzzy Syst. 30 (1), 613–621 (2015).Google Scholar
17. Benzaoui, M., Chekireb, H., Tadjine, M. and Boulkroune, A., “Trajectory tracking with obstacle avoidance of redundant manipulator based on fuzzy inference systems,” Neurocomputing 196 (C), 23–30 (2016).Google Scholar
18. Braganza, D., Dawson, D. M., Walker, I. D. and Nath, N., “A neural network controller for continuum robots,” IEEE Trans. Robot. 23 (6), 1270–1277 (2007).Google Scholar
19. Jasour, A. M. and Farrokhi, M., “Adaptive neuro-predictive control for redundant robot manipulators in presence of static and dynamic obstacles: A lyapunov-based approach,” Int. J. Adapt. Control 28 (3–5), 386–411 (2014).Google Scholar
20. Shang, H., Forbes, J. F. and Guay, M., “Feedback control of hyperbolic distributed parameter systems,” Chem. Eng. Sci. 60 (4), 969–980 (2005).Google Scholar
21. Maidi, A., Jean, P. and Corriou, , “Boundary control of nonlinear distributed parameter systems by input-output linearization,” IFAC Proc. Vol. 44 (1), 10910–10915 (2011).Google Scholar
22. Camarillo, D. B., Milne, C. F., Carlson, C. R., Zinn, M. R. and Salisbury, J. K., “Mechanics modeling of tendon-driven continuum manipulators,” IEEE Trans. Robot. 24 (6), 1262–1273 (2008).Google Scholar
23. Popescu, N., Popescu, D. and Ivanescu, M., “A spatial weight error control for a class of hyper-redundant robots,” IEEE Trans. Robot. 29 (4), 1043–1050 (2013).Google Scholar
24. Kapadia, A. D., Walker, I. D., Dawson, D. M. and Tatlicioglu, E., “A Model-Based Sliding Mode Controller for Extensible Continuum Robots,” Proceedings of the WSEAS International Conference on Signal Processing, Robotics and Automation (2010) pp. 113–120.Google Scholar
25. Rucker, D. C., Rd, W. R., Chirikjian, G. S. and Cowan, N. J., “Equilibrium conformations of concentric-tube continuum robots,” Int. J. Robot. Res. 29 (10), 1263–1280 (2010).Google Scholar
26. Mirosław, G., “Inverse-free control of a robotic manipulator in a task space,” Robot Auton. Syst. 62 (2), 131–141 (2013).Google Scholar
27. Florescu, M., Nguyen, V. D. H. and Ivanescu, M., “Output track controller with gravitational compensation for a class of hyper-redundant robot arms,” Stud. Informat. Control 24 (3), 309–316 (2015).Google Scholar
28. Mu, Z., Liu, T., Xu, W. and Liang, B., “A segmented geometry method of inverse kinematics resolving and configuration planning for spatial hyper-redundant manipulators,” IEEE Trans. Syst. Man Cybernetics Syst. PP (99), 1–11 (2018).Google Scholar