Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-25T09:14:19.955Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic modeling and power optimization of a 4RPSP+PS parallel flight simulator machine

Published online by Cambridge University Press:  16 June 2021

Soheil Zarkandi Open the ORCID record for Soheil Zarkandi [Opens in a new window]
Soheil Zarkandi*
Affiliation:
Department of Mechanical Engineering, Babol Noshirvani University of Technology, Babol, Iran
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Reducing consumed power of a robotic machine has an essential role in enhancing its energy efficiency and must be considered during its design process. This paper deals with dynamic modeling and power optimization of a four-degrees-of-freedom flight simulator machine. Simulator cabin of the machine has yaw, pitch, roll and heave motions produced by a 4RPSP+PS parallel manipulator (PM). Using the Euler–Lagrange method, a closed-form dynamic equation is derived for the 4RPSP+PS PM, and its power consumption is computed on the entire workspace. Then, a newly introduced optimization algorithm called multiobjective golden eagle optimizer is utilized to establish a Pareto front of optimal designs of the manipulator having a relatively larger workspace and lower power consumption. The results are verified through numerical examples.

Keywords

flight simulatorparallel manipulator4 DOFsdynamicsEuler–Lagrange methodSimMechanicspower optimizationgolden eagle optimizer
Type
Article
Information
Robotica , Volume 40 , Issue 3 , March 2022 , pp. 646 - 671
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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

Wikipedia contributors, “Federal Aviation Administration,” Wikipedia, The Free Encyclopedia, https://en.wikipedia. org/w/index.php?title=Federal_Aviation_Administration&oldid=986975477 (accessed November 9, 2020).Google Scholar
Stewart, D., “A platform with six degrees of freedom,” Proc. Inst. Mech. Eng, Part A J. Power Energy 180(15), 371–386 (1965).Google Scholar
Song, Y., Lian, B., Sun, T., Dong, G., Qi, Y. and Gao, H., “A novel five-degree-of-freedom parallel manipulator and its kinematic optimization,” J. Mech. Rob. 6, 041008-1-9 (2014).10.1115/1.4027742CrossRefGoogle Scholar
Zhao, Y., Qiu, K., Wang, Sh. and Zhang, Z., “Inverse kinematics and rigid-body dynamics for a three rotational degrees of freedom parallel manipulator,” Rob. Comput. Integr. Manuf.” 31, 40–50 (2015). doi: 10.1016/j.rcim.2014.07.002 CrossRefGoogle Scholar
Jiang, Y., Li, T.-m. and Wang, L.-p., “Dynamic modeling and redundant force optimization of a 2-DOF parallel kinematic machine with kinematic redundancy,” Rob. Comput. Integr. Manuf. 32, 1–10 (2015). doi: 10.1016/j.rcim.2014.08.001 CrossRefGoogle Scholar
Danaei, B., Arian, A., Tale Masouleh, M. and Kalhor, A., “Dynamic modeling and base inertial parameters determination of a 2-DOF spherical parallel mechanism,” Multibody Syst. Dyn. 41, 367–390 (2017). doi: 10.1007/s11044-017-9578-3 CrossRefGoogle Scholar
Zarkandi, S., “Kinematic and dynamic modeling of a planar parallel manipulator served as CNC tool holder,” Int. J. Dyn. Control 6(1), 14–28 (2018).10.1007/s40435-016-0292-4CrossRefGoogle Scholar
Zarkandi, S., “Kinematics, workspace and optimal design of a novel 4RSS + PS parallel manipulator,” J. Braz. Soc. Mech. Sci. Eng. 41, 474 (2019). doi: 10.1007/s40430-019-1981-7 CrossRefGoogle Scholar
Li, Y., Wang, J., Liu, X.-J. and Wang, L.-P., “Dynamic performance comparison and counterweight optimization of two 3-DOF parallel manipulators for a new hybrid machine tool,” Mech. Mach. Theory 45(11), 1668–1680 (2010). doi: 10.1016/j.mechmachtheory.2010.06.009 CrossRefGoogle Scholar
Liu, S., Huang, T., Mei, J., Zhao, X., Wang, P. and Chetwynd, D. G., “Optimal design of a 4-DOF SCARA type parallel robot using dynamic performance indices and angular constraints,” J. Mech. Rob. 4(3), 031005 (2012). doi: 10.1115/1.4006743 CrossRefGoogle Scholar
Yen, P.-L. and Lai, C.-Ch., “Dynamic modeling and control of a 3-DOF Cartesian parallel manipulator,” Mechatronics 19(3), 390–398 (2009). doi: 10.1016/j.mechatronics.2008.09.007 CrossRefGoogle Scholar
Wu, J., Wang, J., Wang, L. and Li, T., “Dynamics and control of a planar 3-DOF parallel manipulator with actuation redundancy,” Mech. Mach. Theory 44(4), 835–849 (2009). doi: 10.1016/j.mechmachtheory.2008.04.002 CrossRefGoogle Scholar
Yaoa, J., Gua, W., Fenga, Z., Chena, L., Xua, Y. and Zhaoa, Y., “Dynamic analysis and driving force optimization of a 5-DOF parallel manipulator with redundant actuation,” Rob. Comput. Integr. Manuf. 48, 51–58 (2017). doi: 10.1016/j.rcim.2017.02.006 CrossRefGoogle Scholar
Khalil, W. and Guegan, S., “Inverse and direct dynamic modeling of Gough–Stewart manipulators,” IEEE Trans. Rob. 20(4), 754–761 (2004).10.1109/TRO.2004.829473CrossRefGoogle Scholar
Dasgupta, B. and Mruthyunjaya, T. S., “A Newton-Euler formulation for the inverse dynamics of the Stewart platform manipulator,” Mech. Mach. Theory 33(8), 1135–1152 (1998).CrossRefGoogle Scholar
Guo, H. B. and Li, H. R., “Dynamic analysis and simulation of a six degree of freedom Stewart platform manipulator,” Proc. IMechE Vol. 220 Part C: J. Mech. Eng. Sci. 220(1), 61–72 (2006).CrossRefGoogle Scholar
Altuzarra, O., Zubizarreta, A., Cabanes, I. and Pinto, Ch, “Dynamics of a four degrees-of-freedom parallel manipulator with parallelogram joints,” Mechatronics 19(8), 1269–1279 (2009).10.1016/j.mechatronics.2009.08.003CrossRefGoogle Scholar
Akbarzadeh, A. and Enferadi, J., “Improved general solution for the dynamic modeling of Gough–Stewart platform based on principle of virtual work,” J. Intell. Rob. Syst. 63, 25–49 (2011). doi: 10.1007/s11071-015-2489-z CrossRefGoogle Scholar
Liu, M.-J., Li, C.-X. and Li, C.-N., “Dynamics analysis of the Gough–Stewart platform manipulator,” IEEE Trans. Rob. Autom. 16(1), 94–98 (2000).10.1109/70.833196CrossRefGoogle Scholar
Gallardo, J., Rico, J. M. and Frisoli, A., “Dynamics of parallel manipulators by means of screw theory,” Mech. Mach. Theory 38(11), 1113–1131 (2003).CrossRefGoogle Scholar
Akbarzadeh, A., Enferadi, J. and Sharifnia, M., “Dynamics analysis of a 3-RRP spherical parallel manipulator using the natural orthogonal complement,” 29(4), 361–380 (2013).CrossRefGoogle Scholar
Sugimoto, K., “Kinematics and dynamic analysis of parallel manipulator by means of motor algebra,” ASME J. Mech. Transm. Autom. Des. 109(1), 3–7 (1987).10.1115/1.3258783CrossRefGoogle Scholar
Carabin, G., Wehrle, E. and Vidoni, R., “A review on energy-saving optimization methods for robotic and automatic systems,” Robotics 6(39), 1–21 (2017).10.3390/robotics6040039CrossRefGoogle Scholar
Li, Y. and Bone, G. M., Are Parallel Manipulators More Energy Efficient? Proceedings of the 2001 IEEE International Symposium on Computational Intelligence in Robotics and Automation (Cat. No. 01EX515), Banff, AB, Canada (2001) pp. 41–46.Google Scholar
Kim, Y. J., “Design of Low Inertia Manipulator with High Stiffness and Strength using Tension Amplifying Mechanisms,” Proceedings of the IEEE/RSJ International Conference on Intelligent Manipulators and Systems (IROS), Hamburg, Germany (2015) pp. 5850–5856.Google Scholar
Yin, H., Liu, J. and Yang, F., “Hybrid structure design of lightweight robotic arms based on carbon fiber reinforced plastic and aluminum alloy,” IEEE Access 7, 64932–64945(2019). doi: 10.1109/ACCESS.2019.2915363 CrossRefGoogle Scholar
He, Y., Mei, J., Zang, J., Xie, S. and Zhang, F., “Multicriteria optimization design for end effector mounting bracket of a high speed and heavy load palletizing robot,” Math. Problems Eng. 2018, Article ID 6049635, 17 p (2018). doi: 10.1155/2018/6049635 CrossRefGoogle Scholar
Carabin, G., Palomba, I., Wehrle, E. and Vidoni, R., “Energy Expenditure Minimization for a Delta-2 Robot Through a Mixed Approach,” Proceedings of the IFToMMWorld Congress on Mechanism and Machine Science, Krakow, Poland (2019) pp. 383–390.Google Scholar
Khalaf, P. and Richter, H., “Trajectory optimization of manipulators with regenerative drive systems: Numerical and experimental results,” IEEE Trans. Robot 36(2), 501–516 (2019).10.1109/TRO.2019.2923920CrossRefGoogle Scholar
Boscariol, P. and Richiedei, D., “Energy-efficient design of multipoint trajectories for Cartesian manipulators,” Int. J. Adv. Manuf. Technol. 102, 1853–1870 (2019). doi: 10.1007/s00170-018-03234-4 CrossRefGoogle Scholar
Ho, P. M., Uchiyama, N., Sano, S., Honda, Y., Kato, A. and Yonezawa, T., “Simple motion trajectory generation for energy saving of industrial machines,” SICE J. Control Meas. Syst. Integr. 7, 29–34 (2014). doi: 10.1109/SII.2012.6427362 CrossRefGoogle Scholar
Carabin, G., Vidoni, R. and Wehrle, E., “Energy Saving in Mechatronic Systems Through Optimal Point-to-Point Trajectory Generation Via Standard Primitives,” Proceedings of the International Conference of IFToMM ITALY, Cassino, Italy, 29–30 (2018) pp. 20–28.Google Scholar
Lee, G., Park, S., Lee, D., Park, F. C., Jeong, J. I and Kim, J., “Minimizing energy consumption of parallel mechanisms via redundant actuation,” IEEE/ASME Trans. Mech. 20(6), 2805–2812 (2015). doi: 10.1109/TMECH.2015.2401606 CrossRefGoogle Scholar
Lee, G., Sul, S. K. and Kim, J., “Energy-saving method of parallel mechanism by redundant actuation,” Int. J. Precis. Eng. Manuf. Green Tech. 2, 345–351 (2015). doi: 10.1007/s40684-015-0042-7 CrossRefGoogle Scholar
Gómez Ruiz, A., Cavalcanti Santos, J., Croes, J. and Desmet, W., “On redundancy resolution and energy consumption of kinematically redundant planar parallel manipulators,” Robotica 36(6), 809–821 (2018).CrossRefGoogle Scholar
Boscariol, P. and Richiedei, D., “Trajectory design for energy savings in redundant robotic cells,” Robotics 8(1), 15 (2019). doi: 10.3390/robotics8010015 CrossRefGoogle Scholar
Boscariol, P., Scalera, L. and Gasparetto, A., “Task-Dependent Energetic Analysis of a 3 DOF Industrial Manipulator,” Proceedings of the International Conference on Robotics in Alpe-Adria Danube Region, Kaiserslautern, Germany, 19–21 (2019) pp. 162–169.Google Scholar
Scalera, L., Boscariol, P., Carabin, G., Vidoni, R. and Gasparetto, A., “Enhancing energy efficiency of a 4-DOF parallel robot through task-related analysis,” Machines 8(1), 10 (2020). doi: 10.3390/machines8010010 CrossRefGoogle Scholar
Boudreau, R., Léger, J., Tinaou, H. and Gallant, A., “Dynamic analysis and optimization of a kinematically redundant planar parallel manipulator,” Trans. Canad. Soc. Mech. Eng. 42(1), 20–29 (2018). doi: 10.1139/tcsme-2017-0003 CrossRefGoogle Scholar
Park, S., Kim, J. and Lee, G., “Optimal trajectory planning considering optimal torque distribution of redundantly actuated parallel mechanism,” Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci. 232(23), 4410–4419 (2018). doi: 10.1177/0954406217751818 CrossRefGoogle Scholar
Barreto, J. P. and Corves, B., “Matching the Free-Vibration Response of a Delta Robot with Pick-and-Place Tasks Using Multi-Body Simulation,” 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), Munich, Germany (2018) pp. 1487–1492. doi: 10.1109/COASE.2018.8560393 CrossRefGoogle Scholar
Scalera, L., Carabin, G., Vidoni, R. and Wongratanaphisan, T., “Energy efficiency in a 4-DOF parallel robot featuring compliant elements,” Int. J. Mech. Control 20(02), 49–57 (2019).Google Scholar
Liu, X., Bi, W. and Xie, F., “An energy efficiency evaluation method for parallel manipulators based on the kinetic energy change rate,” Sci. China Technol. Sci. 62, 1035–1044 (2019). doi: 10.1007/s11431-019-9487-7 CrossRefGoogle Scholar
Zarkandi, S., “Kinematic analysis and workspace optimization of a novel 4RPSP + PS parallel manipulator,” Mech. Based Des. Struct. Mach. (2020). doi: 10.1080/15397734.2020.1725564 CrossRefGoogle Scholar
Tsai, L.-W., Robot Analysis and Design: The Mechanics of Serial and Parallel Manipulators, Section 9.8 (John Wiley & Sons, Inc., 1999). ISBN:0471325937.Google Scholar
Goldstein, H., Classical Mechanics, 2nd ed. (Addison-Wesley, Reading, MA, 1980).Google Scholar
Mohammadi-Balani, A., Dehghan Nayeri, M., Azar, A. and Taghizadeh-Yazdi, M., “Golden eagle optimizer: A nature-inspired metaheuristic algorithm,” Comput. Ind. Eng. 152 (2021). doi: 10.1016/j.cie.2020.107050 CrossRefGoogle Scholar
Coello Coello, C. A. and Lechuga, M. S., “MOPSO: A Proposal for Multiple Objective Particle Swarm Optimization,” Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02 (Cat. No.02TH8600), Honolulu, HI, USA, vol. 2 (2002) pp. 1051–1056. doi: 10.1109/CEC.2002.1004388 CrossRefGoogle Scholar