Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-27T14:52:57.899Z Has data issue: false hasContentIssue false
  • English
  • Français

A redundant dynamic model of parallel robots for model-based control

Published online by Cambridge University Press:  22 May 2012

Asier Zubizarreta ,
Itziar Cabanes ,
Marga Marcos  and
Charles Pinto
Asier Zubizarreta
Affiliation:
Department of Automatic Control and System Engineering, University of the Basque Country, Spain
Itziar Cabanes*
Affiliation:
Department of Automatic Control and System Engineering, University of the Basque Country, Spain
Marga Marcos
Affiliation:
Department of Automatic Control and System Engineering, University of the Basque Country, Spain
Charles Pinto
Affiliation:
Department of Mechanical Engineering, University of the Basque Country, Spain
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

The use of extra sensors in parallel robots can provide an increase in control performance, making it possible to fully exploit the potential of these mechanisms. In this paper, a comprehensive redundant dynamic modelling procedure for the six-degree-of-freedom Gough platform is presented. The proposed methodology makes it possible to define the model in terms of all sensorized joint variables in order to implement redundant information-based control, and an example, the Extended Computed Torque Control (Extended CTC) approach, is developed. This, applied to parallel robots, ensures better dynamic performance than the traditional CTC approach. In order to validate dynamic modelling, a two-step procedure is used in this paper. First, the redundant dynamic model is validated by comparing its dynamic performance with the previous research in the field. Second, an exhaustive study is carried out that demonstrates the advantages of the redundant dynamic model when used in the Extended CTC approach.

Keywords

Robot dynamicsControl of robotic systemsMechatronic systemsParallel manipulatorsSensor networks
Type
Articles
Information
Robotica , Volume 31 , Issue 2 , March 2013 , pp. 203 - 216
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Abdellatif, H. and Heimann, B., “Computational efficient inverse dynamics of 6-dof fully parallel manipulators by using the lagrangian formalism,” Mech. Mach. Theory 44, 192–207 (2009).CrossRefGoogle Scholar
2.Angeles, J., Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms (Springer, New York, 2007).CrossRefGoogle Scholar
3.Aracil, R., Saltaren, R. and Reinoso, O., “A climbing parallel robot: A robot to climb along tubular and metallic structures,” Robot. Autom. Mag. 13 (1), 16–22 (2006).CrossRefGoogle Scholar
4.Baron, L. and Angeles, J., “The kinematic decoupling of parallel manipulators using joint-sensor data,” IEEE Trans. Robot. Autom. 16 (6), 644–651 (2000).CrossRefGoogle Scholar
5.Bauma, V., Valášek, M. and Sika, Z., “Increase of PKM Positioning Accuracy by Redundant Measurement,” In: Proceedings of the 5th Chemnitzer Parallel Kinematik Seminar, Chemnitz, Germany (2006) pp. 547–564.Google Scholar
6.Bhattacharya, S., Hatwal, H. and Ghosh, A., “An on-line parameter estimation scheme for generalized stewart platform-type parallel manipulators,” Mech. Mach. Theory 32 (1), 79–89 (1997).CrossRefGoogle Scholar
7.Bhattacharya, S., Nenchev, N. and Uchiyama, M., “A recursive formula for the inverse of the inertia matrix of a parallel manipulator,” Mech. Mach. Theory 33 (7), 957–964 (1998).CrossRefGoogle Scholar
8.Cabanes, I., Zubizarreta, A., Marcos, M. and Pinto, C., “Real Time Distributed Control of Parallel Robots Using Redundant Sensors,” In: Proceedings of the 40th International Symposium on Robotics, Barcelona, Spain (2009) pp. 139–144.Google Scholar
9.Dasgupta, B. and Mruthyunjaya, T., “A Newton–Euler formulation for the inverse dynamics of the stewart platform,” Mech. Mach. Theory 33 (8), 1135–1152 (1998).CrossRefGoogle Scholar
10.Dasgupta, B. and Mruthyunjaya, T., “The stewart platform manipulator: A review,” Mech. Mach. Theory 35 (1), 15–40 (2000).CrossRefGoogle Scholar
11.Do, W. Q. D. and Yang, D. C. H., “Inverse dynamic analysis and simulation of a platform type of robot,” J. Robot. Syst. 5 (3), 209–227 (1988).CrossRefGoogle Scholar
12.Dwarakanath, T., Dasgupta, B. and Mruthyunjaya, T., “Design and development of a stewart platform-based force-torque sensor,” Mechatronics 11 (7), 793–809 (2001).CrossRefGoogle Scholar
13.Fu, S. and Ya, Y., “Non-linear robust control with partial inverse dynamic compensation for a stewart platform manipulator,” Int. J. Modelling Identif. Control 1 (1), 44–51 (2006).CrossRefGoogle Scholar
14.Gallardo, J., Rico, J. M., Frisoli, A., Checcacci, D. and Bergamasco, M., “Dynamics of parallel manipulators by means of screw theory,” Mech. Mach Theory 38, 1113–1131 (2003).CrossRefGoogle Scholar
15.Geike, T. and McPhee, J., “Inverse dynamic analysis of parallel manipulators with full mobility,” Mech. Mach. Theory 38, 549–562 (2003).CrossRefGoogle Scholar
16.Ghobakhloo, A., Eghtesad, M. and Azadi, M., “Position Control of a Stewart–Gough Platform Using Inverse Dynamics Method with Full Dynamics,” In: Proceedings of the 9th IEEE International Workshop on Advanced Motion Control, Istanbul, Turkey (2006) pp. 50–55.Google Scholar
17.Ghorbel, F., Chételat, O., Gunawardana, R. and Longchamp, R., “Modeling and set point control of closed-chain mechanisms: Theory and experiment,” IEEE Trans. Control Syst. Tech. 8 (5), 801–815 (2000).CrossRefGoogle Scholar
18.Gough, V. and Whitehall, S., “Universal Tyre Test Machine,” In: Proceedings of the FISITA Ninth International Technical Congress, London (May, 1962) pp. 117–137.Google Scholar
19.Guo, H. and Li, H., “Dynamic analysis and simulation of a six degree of freedom stewart platform manipulator,” Proc. IMechE C: J. Mech. Eng. Sci. 220, 61–72 (2006).CrossRefGoogle Scholar
20.Guo, H. B., Liu, Y., Liu, G. and Li, H., “Cascade control of a hydraulically driven 6-DOF parallel robot manipulator based on a sliding mode,” Control Eng. Pract. 16 (9), 1055–1068 (2008).CrossRefGoogle Scholar
21.Hopkins, B. R. and Williams II, R. L., “Kinematics, design and control of the 6-psu platform,” Ind. Robot Int. J. 29 (5), 443–451 (2002).CrossRefGoogle Scholar
22.Huang, C.-I., Chang, C.-F., Yu, M.-Y. and Fu, L.-C., “Sliding-mode tracking control of the stewart platform,” 5th Asian Control Conf. 1, 562–569 (2004).Google Scholar
23.Iqbal, S., Bhatti, A. I. and Ahmed, Q., “Dynamic Analysis and Robust Control Design for Stewart Platform with Moving Payloads,” In: Proceedings of the 17th World Congress of the International Federation of Automatic Control (IFAC 2008), COEX, South Korea (2008) pp. 5324–5329.Google Scholar
24.Khalil, W. and Guegan, S., “Inverse and direct dynamic modeling of gough-stewart robots,” IEEE Trans. Robot 20 (4), 754–762 (2004).CrossRefGoogle Scholar
25.Kim, D. H., Kang, J-Y. and Lee, K.-I., “Robust tracking control design for a 6 dof parallel manipulator,” J. Robot. Syst. 17 (10), 527–547 (2000).3.0.CO;2-A>CrossRefGoogle Scholar
26.Kim, N.-I. and Lee, C.-W., “High-Speed Tracking Control of Stewart Platform Manipulator via Enhanced Sliding Mode Control,” In: Proceedings of the IEEE International Conference in Robotics and Automation, Leuven, Belgium (May 1998) pp. 2716–2721.Google Scholar
27.Lebret, G., Liu, K. and Lewis, F. L., “Dynamic analysis and control of a stewart platform manipulators,” J. Robot. Syst. 10 (5), 629–655 (1993).CrossRefGoogle Scholar
28.Lee, S.-H., Song, J.-B., Choi, W.-C. and Hong, D., “Position control of a stewart platform using inverse dynamics control with approximate dynamics,” Mechatronics 13, 605–619 (2003).CrossRefGoogle Scholar
29.Li, D. and Salcudean, S., “Modeling, simulation and control of a hydraulic stewart platform,” IEEE Int. Conf. Robot. Autom. 4, 3360–3366 (1997).Google Scholar
30.Marquet, F., Company, O., Krut, S. and Pierrot, F., “Enhancing Parallel Robots Accuracy with Redundant Sensors,” In: Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Minnesota, USA (2002) pp. 4114–4119.Google Scholar
31.Merlet, J. P., “Closed form resolution of the direct kinematics of parallel manipulators using extra sensors data,” In: Proceedings of the IEEE International Conference in Robotics and Automation, Atlanta, GA (1993) pp. 200–304.Google Scholar
32.Merlet, J. P.,” Parallel Robots, 2nd. ed (Kluwer, London, UK, 2006).Google Scholar
33.Nakadate, R., Uda, H., Hirano, H., Solis, J., Takanishi, A., Minagawa, E., Sugawara, M. and Niki, K., “Development of a Robotic Carotid Blood Measurement Wta-1rii: Mechanical Improvement of Gravity Compensation Mechanism and Optimal link Position of the Parallel Manipulator Based on ga,” In: Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Singapore (Jul. 2009) pp. 717–722.Google Scholar
34.Nakamura, Y. and Godoussi, M., “Dynamics computation of closed-link robot mechanisms with nonredundant and redundant actuators,” IEEE Trans. Robot. Autom. 5 (3), 294–302, (1989).CrossRefGoogle Scholar
35.Omran, A., El-Bayiumi, G., Bayoumi, M. and Kassem, A., “Genetic algorithm-based optimal control for a 6-DOF non-redundant Stewart manipulator,” Int. J. Mech. Ind. Aerosp. Eng. 2 (2), 73–79 (2008).Google Scholar
36.Parenti-Castelli, V. and Gregorio, R. D., “A new algorithm based on two extra-sensors for real-time computation of the actual configuration of the generalized Stewart-Gough manipulator,” J. Mech. Des. 122 (1), 294–298 (2000).CrossRefGoogle Scholar
37.Riebe, S. and Ulbrich, H., “Modelling and online computation of the dynamics of a parallel kinematic with six degrees-of-freedom,” Arch. Appl. Mech. 72, 813–829 (2003).CrossRefGoogle Scholar
38.Stewart, D., “A platform with six degrees of freedom,” Proc. IMechE 180, 371–385 (1965–1966).CrossRefGoogle Scholar
39.Su, Y. and Duan, B., “The application of the Stewart platform in large spherical radio telescopes,” J. Robot. Syst. 17 (7), 375–383 (2000).3.0.CO;2-7>CrossRefGoogle Scholar
40.Su, Y. X., Duan, B. Y., Zheng, C. H., Zhang, Y. F., Chen, G. D. and Mi, J. W., “Disturbance-rejection high-precision motion control of a stewart platform,” IEEE Trans. Control Syst. Tech. 12 (3), 364–374 (2004).CrossRefGoogle Scholar
41.Tsai, L.-W., “Solving the inverse dynamics of a Stewart-Gough manipulator by the principle of virtual work,” ASME J. Mech. Des. 122, 3–9 (2000).CrossRefGoogle Scholar
42.Wang, J. and Gosselin, C., “A new approach for the dynamic analysis of parallel manipulator,” Multibody Syst. Dyn. 2, 317–334 (1998).CrossRefGoogle Scholar
43.Yang, C., Huang, Q., Jiang, H., Peter, O. O. and Han, J., “Pd control with gravity compensation for hydraulic 6-dof parallel manipulator,” Mech. Mach. Theory 45 (4), 666–677 (2010).CrossRefGoogle Scholar
44.Zubizarreta, A., Cabanes, I., Marcos, M. and Pinto, C., “Control of Parallel Robots Using Passive Sensor Data,” In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS 2008), Nice, France (Sep. 22–26, 2008) pp. 2398–2403.Google Scholar
45.Álvarez, C., Saltarén, R., Aracil, R. and García, C., “Concepción, desarrollo y avances en el control de navegación de robots submarinos paralelos: El robot remo-i,” Revista Iberoamericana de Automática e Informática 6 (3), 92–100 (2009) (in Spanish).CrossRefGoogle Scholar