Adaptive Impedance Control Method for Dynamic Contact Force Tracking of Robotic Excavators
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 11
Abstract
Robotic excavators commonly are used in industrial and construction tasks to improve efficiency and shorten construction periods, but they have high energy consumption and vibration and shock problems, the greatest of which is impact phenomenon in contact with construction environment. A perfect construction task with low vibration and high precision can be achieved only by skilled operators, and requires very intense concentration. Due to the urgent labor shortage caused by the pandemic, tight schedules, and increasingly complex construction projects, it is important for construction management to have an intelligent control method that combines the force and position of excavators in the construction progress. This study developed an adaptive impedance control method to realize coordinated control of force and position. An adaptive impedance control was designed to adjust the impedance parameters indirectly. Three different simulations were conducted to compare the force tracking performance of the classic impedance control and the proposed adaptive impedance control, namely, environmental location changes, environmental stiffness changes, and dynamic force tracking. Blended contact surfaces were designed to validate the performance of the control algorithms. Results show that the proposed adaptive impedance control effectively improved the force tracking accuracy. This paper offers an original contribution to the intelligent control method of excavator construction, and will be of use to operators, especially in large ground, mine, earthquake, and other complex ground construction sites. In addition, the research also provides construction manager and other practitioners with an impedance control method in construction project management that can save labor cost, improve production efficiency, and accelerate the transformation to a digital and intelligent construction industry.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (52105064), the Natural Science Foundation of Jiangsu Province (BK20221342), the National Key Research and Development Program of China (2021YFB2011904), and the Research Start-up Fund of NUIST (2021R042).
References
Allain, M., S. Konduri, H. Maske, P. R. Pagilla, and G. Chowdhary. 2017. “Blended shared control of a hydraulic excavator.” IFAC-Papersonline 50 (1): 14928–14933. https://doi.org/10.1016/j.ifacol.2017.08.2541.
Bartlett, H. L., S. T. King, M. Goldfarb, and B. E. Lawson. 2022. “Design and assist-as-needed control of a lightly powered prosthetic knee.” IEEE Trans. Med. Rob. Bionics 4 (2): 490–501. https://doi.org/10.1109/TMRB.2022.3161068.
Calanca, A., R. Muradore, and P. Fiorini. 2017. “Impedance control of series elastic actuators: Passivity and acceleration-based control.” Mechatronics 47 (Nov): 37–48. https://doi.org/10.1016/j.mechatronics.2017.08.010.
Çelik, D., and M. E. Meral. 2022. “A coordinated virtual impedance control scheme for three phase four leg inverters of electric vehicle to grid (V2G).” Energy 246 (May): 123354. https://doi.org/10.1016/j.energy.2022.123354.
Dong, C., Z. Yu, X. Chen, H. Chen, Y. Huang, and Q. Huang. 2022. “Adaptability control towards complex ground based on fuzzy logic for humanoid robots.” IEEE Trans. Fuzzy Syst. 30 (6): 1574–1584. https://doi.org/10.1109/TFUZZ.2022.3167458.
Duan, J. Y., Y. Gan, M. Chen, and X. Dai. 2018. “Adaptive variable impedance control for dynamic contact force tracking in uncertain environment.” Rob. Auton. Syst. 102 (Apr): 54–65. https://doi.org/10.1016/j.robot.2018.01.009.
Edwards, D. J., and G. D. Holt. 2011. “Mini-excavator safety: Toward innovative stability testing, procurement, and manufacture.” J. Constr. Eng. Manage. 137 (12): 1125–1133. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000383.
Fateh, M. M. 2010. “Robust impedance control of a hydraulic suspension system.” Int. J. Robust Nonlinear 20 (8): 858–872. https://doi.org/10.1002/rnc.1473.
Feng, H., W. Ma, C. Yin, and D. Cao. 2021a. “Trajectory control of electro-hydraulic position servo system using improved PSO-PID controller.” Autom. Constr. 127 (Jul): 103722. https://doi.org/10.1016/j.autcon.2021.103722.
Feng, H., W. Qiao, C. Yin, H. Yu, and D. Cao. 2019. “Identification and compensation of non-linear friction for a electro-hydraulic system.” Mech. Mach. Theory 141 (Nov): 1–13. https://doi.org/10.1016/j.mechmachtheory.2019.07.004.
Feng, Z., W. Liang, J. Ling, X. Xiao, and H. L. Tong. 2021b. “Adaptive robust impedance control for an ear surgical device with soft interaction.” IEEE/ASME Trans. Mech. 27 (3): 1784–1795. https://doi.org/10.1109/TMECH.2021.3087014.
Fu, Y., X. Han, N. Sepehri, G. Zhou, J. Fu, L. Yu, and R. Yang. 2018. “Design and performance analysis of position-based impedance control for an electrohydrostatic actuation system.” Chin. J. Aeronaut. 31 (3): 584–596. https://doi.org/10.1016/j.cja.2017.08.015.
Ganjefar, S., S. Rezaei, and F. Hashemzadeh. 2017. “Position and force tracking in nonlinear teleoperation systems with sandwich linearity in actuators and time-varying delay.” Mech. Syst. Signal Process. 86 (Mar): 308–324. https://doi.org/10.1016/j.ymssp.2016.09.023.
Gierlak, P., and M. Szuster. 2017. “Adaptive position/force control for robot manipulator in contact with a flexible environment.” Rob. Auton. Syst. 95 (Sep): 80–101. https://doi.org/10.1016/j.robot.2017.05.015.
Ha, Q. P., Q. H. Nguyen, D. C. Rye, and H. F. Durrant-Whyte. 2000. “Impedance control of a hydraulically actuated robotic excavator.” Autom. Constr. 9 (5–6): 421–435. https://doi.org/10.1016/S0926-5805(00)00056-X.
Hongan, N. 1985. “Impedance control an approach to manipulation: I-theory. II-implementation. III-application.” J. Dyn. Syst. Meas. Control 107 (Mar): 1–24. https://doi.org/10.1115/1.3140713.
Kang, S., H. Yan, L. Dong, and C. Li. 2018. “Finite-time adaptive sliding mode force control for electro-hydraulic load simulator based on improved GMS friction model.” Mech. Syst. Signal Process. 102 (Mar): 117–138. https://doi.org/10.1016/j.ymssp.2017.09.009.
Kim, J., D.-E. Lee, and J. Seo. 2020. “Task planning strategy and path similarity analysis for an autonomous excavator.” Autom. Constr. 112 (Mar): 103108. https://doi.org/10.1016/j.autcon.2020.103108.
Lakshminarayanan, S., S. Kana, D. M. Mohan, O. M. Manyar, D. Then, and D. Campolo. 2021. “An adaptive framework for robotic polishing based on impedance control.” Int. J. Adv. Manuf. Technol. 112 (1): 401–417. https://doi.org/10.1007/s00170-020-06270-1.
Li, X., Y.-H. Liu, and H. Yu. 2018. “Iterative learning impedance control for rehabilitation robots driven by series elastic actuators.” Automatica 90 (Apr): 1–7. https://doi.org/10.1016/j.automatica.2017.12.031.
Li, Z., Z. Huang, W. He, and C.-Y. Su. 2017. “Adaptive impedance control for an upper limb robotic exoskeleton using biological signals.” IEEE Trans. Ind. Electron. 64 (2): 1664–1674. https://doi.org/10.1109/TIE.2016.2538741.
Mustaffa, N. K. 2022. “Alternative configurations of earthmoving loading practices toward emissions reduction.” J. Constr. Eng. Manage. 148 (1): 04021177. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002211.
Mustalahti, P., and J. Mattila. 2022. “Position-based impedance control design for a hydraulically actuated series elastic actuator.” Energies 15 (7): 2503. https://doi.org/10.3390/en15072503.
Navvabi, H., and A. H. D. Markazi. 2019. “Hybrid position/force control of Stewart Manipulator using extended adaptive fuzzy sliding mode controller (E-AFSMC).” ISA Trans. 88 (May): 280–295. https://doi.org/10.1016/j.isatra.2018.11.037.
Oh, S., and K. Kong. 2017. “High-precision robust force control of a series elastic actuator.” IEEE/ASME Trans. Mechatron. 22 (1): 71–80. https://doi.org/10.1109/TMECH.2016.2614503.
Raibert, M. H., and J. J. Craig. 1981. “Hybrid position/force control of manipulators.” ASME J. Dyn. Syst. Meas. Control 103 (2): 126–133. https://doi.org/10.1115/1.3139652.
Reginald, N., J. Seo, and M. Cha. 2021. “Integrative tracking control strategy for robotic excavation.” Int. J. Control Autom. 19 (10): 3435–3450. https://doi.org/10.1007/s12555-020-0595-2.
Sabahi, F. 2017. “Introducing validity into self-organizing fuzzy neural network applied to impedance force control.” Fuzzy Sets Syst. 337 (Apr): 113–127. https://doi.org/10.1016/j.fss.2017.09.007.
Sandzimier, R. J., and H. H. Asada. 2020. “A data-driven approach to prediction and optimal bucket-filling control for autonomous excavators.” IEEE Rob. Autom. Lett. 5 (2): 2682–2689. https://doi.org/10.1109/LRA.2020.2969944.
Shahriari, E., S. A. B. Birjandi, and S. Haddadin. 2022. “Passivity-based adaptive force-impedance control for modular multi-manual object manipulation.” IEEE Rob. Autom. Lett. 7 (2): 2194–2201. https://doi.org/10.1109/LRA.2022.3142903.
Sharifi, M., S. Behzadipour, H. Salarieh, and M. Tavakoli. 2017. “Cooperative modalities in robotic tele-rehabilitation using nonlinear bilateral impedance control.” Control Eng. Pract. 67 (Oct): 52–63. https://doi.org/10.1016/j.conengprac.2017.07.002.
Shen, X., E. Marks, N. Pradhananga, and T. Cheng. 2016. “Hazardous proximity zone design for heavy construction excavation equipment.” J. Constr. Eng. Manage. 142 (6): 05016001. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001108.
Tafazoli, S., S. E. Salcudean, K. Hashtrudi-Zaad, and P. D. Lawrence. 2002. “Impedance control of a teleoperated excavator.” IEEE Trans. Control Syst. Technol. 10 (3): 355–367. https://doi.org/10.1109/87.998021.
Wang, S., S. Zhu, and P. L. Yuen. 2021. “Assessment of ground-borne vibration impact on nearby underground facilities induced by ground surface excavation.” J. Constr. Eng. Manage. 147 (7): 04021071. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002065.
Ye, Y., C.-B. Yin, Y. Gong, and J.-J. Zhou. 2017. “Position control of nonlinear hydraulic system using an improved PSO based PID controller.” Mech. Syst. Signal Process. 83 (Jan): 241–259. https://doi.org/10.1016/j.ymssp.2016.06.010.
Zhai, A., H. Zhang, J. Wang, G. Lu, J. Li, and S. Chen. 2022. “Adaptive neural synchronized impedance control for cooperative manipulators processing under uncertain environments.” Rob. Comput. Integr. Manuf. 75 (Jun): 102291. https://doi.org/10.1016/j.rcim.2021.102291.
Zhang, X., T. Sun, and D. Deng. 2020. “Neural approximation-based adaptive variable impedance control of robots.” Trans. Inst. Meas. Control 42 (13): 2589–2598. https://doi.org/10.1177/0142331220932649.
Zhu, H., B.-G. Hwang, J. Ngo, and J. P. S. Tan. 2022a. “Applications of smart technologies in construction project management.” J. Constr. Eng. Manage. 148 (4): 04022010. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002260.
Zhu, Q., D. Huang, B. Yu, K. Ba, X. Kong, and S. Wang. 2022b. “An improved method combined SMC and MLESO for impedance control of legged robots’ electro-hydraulic servo system.” ISA Trans. https://doi.org/10.1016/j.isatra.2022.03.009.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 148 • Issue 11 • November 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jan 19, 2022
Accepted: Jun 29, 2022
Published online: Sep 7, 2022
Published in print: Nov 1, 2022
Discussion open until: Feb 7, 2023
ASCE Technical Topics:
- Adaptive systems
- Business management
- Construction engineering
- Construction management
- Construction methods
- Construction sites
- Contact mechanics
- Continuum mechanics
- Deformation (mechanics)
- Detection methods
- Engineering fundamentals
- Engineering mechanics
- Excavation
- Management methods
- Methodology (by type)
- Practice and Profession
- Solid mechanics
- Structural mechanics
- Systems engineering
- Systems management
- Tracking
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Sambo Lyson Zulu, Ali M. Saad, Barry Gledson, Exploring Leaders’ Perceptions of the Business Case for Digitalisation in the Construction Industry, Buildings, 10.3390/buildings13030701, 13, 3, (701), (2023).