Multi-objective Design Optimization and Control Strategy for Digital Hydraulically Driven Knee Exoskeleton

Authors

DOI:

https://doi.org/10.13052/ijfp1439-9776.2425

Keywords:

Knee exoskeleton, Hydraulic drives, Digital hydraulics, Design optimization

Abstract

This article presents a multi-objective design optimization strategy to determine an optimal design of digital hydraulically driven knee exoskeleton. To satisfy the overall goal of compact and lightweight design, four key design objectives are defined. Via genetic algorithm based multi-objective optimization technique, the pareto-optimal set of designs is determined and the trade-offs between the design objectives are analysed. Via decisions based on component availability and user-comfort, the dimensionality of the pareto-front is reduced to two and an exoskeleton design is selected that offers a good compromise between the design objectives.

For the actuation of the exoskeleton, an energy efficient control strategy is proposed which consists of using passive control during the stance phase and simplified model predictive control during the swing phase. The operation of the chosen knee exoskeleton design and the control strategy is investigated via numerical simulations. The results indicate that the exoskeleton successfully tracks the desired knee motion and delivers the required knee torque.

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Author Biographies

Rituraj, Institute of Machine Design and Hydraulic Drives, Johannes Kepler University, Linz, Austria

Rituraj received his B.Tech. degree from IIT Guwahati, India in 2013 and his Ph.D. degree from Purdue University, USA in 2020. During his direct-Ph.D. at Maha Fluid Power Research Center, he worked on numerical modelling of External Gear Machines. Currently, he is a postdoctoral researcher at Institute of Machine Design and Hydraulic Drives in JKU, Austria where he is working on the development of hydraulically driven exoskeletons. His overall research interests include numerical and experimental study of hydraulic components and systems.

Rudolf Scheidl, Institute of Machine Design and Hydraulic Drives, Johannes Kepler University, Linz, Austria

Rudolf Scheidl received his M.Sc. of Mechanical Engineering and Doctor of Engineering Sciences degrees at Vienna University of Technology. He has research and development experience in agricultural machinery (Epple Buxbaum Werke), continuous casting technology (Voest-Alpine Industrieanlagenbau) and paper mills (Voith). Since 1990, he is a full Professor of Mechanical Engineering at Johannes Kepler University, Austria. His research topics include hydraulic drive technology and mechatronic design.

References

J.A. de la Tejera, R. Bustamante-Bello, R.A. Ramirez-Mendoza, J. Izquierdo-Reyes, Systematic Review of Exoskeletons towards a General Categorization Model Proposal, Appl. Sci. 11 (2021) 76. https://doi.org/10.3390/app11010076.

R. Scheidl, Digital fluid power for exoskeleton actuation – guidelines, opportunities, challenges, in: Ninth Workshop Digit. Fluid Power, Aalborg, Denmark, 2017.

H. Kazerooni, J.-L. Racine, L. Huang, R. Steger, On the Control of the Berkeley Lower Extremity Exoskeleton (BLEEX), in: Proc. 2005 IEEE Int. Conf. Robot. Autom., 2005: pp. 4353–4360. https://doi.org/10.1109/ROBOT.2005.1570790.

J. Ghan, R. Steger, H. Kazerooni, Control and system identification for the Berkeley lower extremity exoskeleton (BLEEX), Adv. Robot. 20 (2006) 989–1014. https://doi.org/10.1163/156855306778394012.

A.B. Zoss, H. Kazerooni, A. Chu, Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX), IEEEASME Trans. Mechatron. 11 (2006) 128–138. https://doi.org/10.1109/TMECH.2006.871087.

W. Huo, S. Mohammed, J.C. Moreno, Y. Amirat, Lower Limb Wearable Robots for Assistance and Rehabilitation: A State of the Art, IEEE Syst. J. 10 (2016) 1068–1081. https://doi.org/10.1109/JSYST.2014.2351491.

Y. Yang, X. Dong, X. Liu, D. Huang, Robust Repetitive Learning-Based Trajectory Tracking Control for a Leg Exoskeleton Driven by Hybrid Hydraulic System, IEEE Access. 8 (2020) 27705–27714. https://doi.org/10.1109/ACCESS.2020.2971777.

J. Jiang, Y. Wang, H. Cao, J. Zhu, X. Zhang, A novel pump-valve coordinated controlled hydraulic system for the lower extremity exoskeleton, Trans. Inst. Meas. Control. 42 (2020) 2872–2884. https://doi.org/10.1177/0142331220930623.

T. Kosaki, S. Li, A Water-Hydraulic Upper-Limb Assistive Exoskeleton System with Displacement Estimation, J. Robot. Mechatron. 30 (2020) 149–156.

R. Scheidl, M. Linjama, S. Schmidt, Is the future of fluid power digital?, Proc. Inst. Mech. Eng. Part J. Syst. Control Eng. 226 (2012) 721–723. https://doi.org/10.1177/0959651811435628.

H. Cao, Z. Ling, J. Zhu, Y. Wang, W. Wang, Design frame of a leg exoskeleton for load-carrying augmentation, in: 2009 IEEE Int. Conf. Robot. Biomim. ROBIO, 2009: pp. 426–431. https://doi.org/10.1109/ROBIO.2009.5420684.

E. Holl, R. Scheidl, S. Eshkabilov, Simulation Study of a Digital Hydraulic Drive for a Knee Joint Exoskeleton, in: Proc. ASMEBATH 2017 Symp. Fluid Power Motion Control, Sarasota, Florida, USA, 2017. https://doi.org/10.1115/FPMC2017-4220.

R. Rituraj, R. Scheidl, P. Ladner, M. Lauber, A Novel Design Concept of Digital Hydraulic Drive for Knee Exoskeleton, in: Proc. ASMEBATH 2021 Symp. Fluid Power Motion Control, Virtual, Online, 2021. https://doi.org/10.1115/FPMC2021-68590.

HAWE Micro Fluid GmbH, (2022). www.hawe.com.

M. Linjama, M. Paloniitty, L. Tiainen, K. Huhtala, Mechatronic Design of Digital Hydraulic Micro Valve Package, Procedia Eng. 106 (2015) 97–107. https://doi.org/10.1016/j.proeng.2015.06.013.

J. Wojtusch, O. von Stryk, HuMoD – A versatile and open database for the investigation, modeling and simulation of human motion dynamics on actuation level, in: 2015 IEEE-RAS 15th Int. Conf. Humanoid Robots Humanoids, 2015: pp. 74–79. https://doi.org/10.1109/HUMANOIDS.2015.7363534.

HuMoD, (n.d.). https://www.sim.informatik.tu-darmstadt.de/res/ds/humod/.

F.N. Fritsch, R.E. Carlson, Monotone Piecewise Cubic Interpolation, SIAM J. Numer. Anal. 17 (1980) 238–246. https://doi.org/10.1137/0717021.

K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput. 6 (2002) 182–197. https://doi.org/10.1109/4235.996017.

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Published

2023-05-03

How to Cite

Rituraj, & Scheidl, R. . (2023). Multi-objective Design Optimization and Control Strategy for Digital Hydraulically Driven Knee Exoskeleton. International Journal of Fluid Power, 24(02), 271–298. https://doi.org/10.13052/ijfp1439-9776.2425

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Section

IFK2022

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