Skip to main content
SpringerLink
Log in

A Review on Robust Control of Robot Manipulators for Future Manufacturing

  • Review
  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

Robots are used for many manufacturing tasks, and its prevalence in manufacturing is ever-increasing. Robots in future manufacturing are expected to be valuable and essential tools. It is difficult to control a robot to achieve assigned tasks because of the nonlinear time-varying coupled multi-input multi-output dynamics, nonlinear joint friction being difficult to estimate and compensate for, and variations in payload and in environmental dynamics. Further, from the manufacturing engineers’ point of view, the controller needs to be simple and intuitive to understand and implement in practice. One such controller is Time Delay Control, which has been used for more than three decades with many advances. The time-delay estimation allows us to estimate the unknown/uncertain robot dynamics and disturbances by just using the most recent past control torque and acceleration, alleviating the need to identify robot dynamics and/or its parameters for the design of the controller. Time Delay Control can be implemented in industrial controllers allowing only proportional-integral-derivative control thanks to the gain relationship between Time Delay Control and proportional-integral-derivative control; has built-in first-order low-pass filter reducing noise; can be equipped with a simple anti-windup scheme for increasing its stability. A brief comparison of Time Delay Control and Disturbance Observer is also provided for readers who are interested in various robust control. With the introduction and review of the Time Delay Control for a robot, it is expected that the readers’ understanding of this robust control is increased and the use of the Time Delay Control in manufacturing becomes prevalent.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Wang, W., Guo, Q., Yang, Z., Jiang, Y., & Xu, J. (2023). A state-of-the-art review on robotic milling of complex parts with high efficiency and precision. Robotics and Computer-Integrated Manufacturing, 79, 102436. https://doi.org/10.1016/j.rcim.2022.102436

    Article  Google Scholar 

  2. Wu, K., Li, J., Zhao, H., & Zhong, Y. (2022). Review of industrial robot stiffness identification and modelling. Applied Sciences, 12(17), 8719.

    Article  Google Scholar 

  3. Chen, X., & Zhan, Q. (2021). The kinematic calibration of a drilling robot with optimal measurement configurations based on an improved multi-objective PSO algorithm. International Journal of Precision Engineering and Manufacturing, 22(9), 1537–1549. https://doi.org/10.1007/s12541-021-00556-4

    Article  Google Scholar 

  4. Song, K., Xiao, G., Chen, S., Liu, X., & Huang, Y. (2023). A new force-depth model for robotic abrasive belt grinding and confirmation by grinding of the Inconel 718 alloy. Robotics and Computer-Integrated Manufacturing, 80, 102483. https://doi.org/10.1016/j.rcim.2022.102483

    Article  Google Scholar 

  5. Kazerooni, H. (1988). Automated robotic deburring using impedance control. IEEE Control Systems Magazine, 8(1), 21–25. https://doi.org/10.1109/37.464

    Article  MathSciNet  Google Scholar 

  6. Basanez, L., & Rosell, J. (2005). Robotic polishing systems. IEEE Robotics & Automation Magazine, 12(3), 35–43. https://doi.org/10.1109/MRA.2005.1511867

    Article  Google Scholar 

  7. Ke, X., Yu, Y., Li, K., Wang, T., Zhong, B., Wang, Z., Kong, L., Guo, J., Huang, L., Idir, M., Liu, C., & Wang, C. (2023). Review on robot-assisted polishing: Status and future trends. Robotics and Computer-Integrated Manufacturing, 80, 102482. https://doi.org/10.1016/j.rcim.2022.102482

    Article  Google Scholar 

  8. Chan, S. P., & Liaw, H. C. (1996). Generalized impedance control of robot for assembly tasks requiring compliant manipulation. IEEE Transactions on Industrial Electronics, 43(4), 453–461. https://doi.org/10.1109/41.510636

    Article  Google Scholar 

  9. Yoon, J.-S., Kim, Y.-D., Lee, J., & Lee, D. Y. (2023). OPC UA-based machining cell monitoring system for multi-vendors’ machine tools and industrial robots. Int J Precis Eng Manuf-Smart Tech, 1(1), 63–69. https://doi.org/10.57062/ijpem-st.2022.0024

    Article  Google Scholar 

  10. Lee, J., Chua, P. C., Chen, L., Ng, P. H. N., Kim, Y., Wu, Q., Jeon, S., Jung, J., Chang, S., & Moon, S. K. (2023). Key enabling technologies for smart factory in automotive industry: Status and applications. International Journal of Precision Engineering and Manufacturing-Smart Technology, 1(1), 93–105. https://doi.org/10.57062/ijpem-st.2022.0017

    Article  Google Scholar 

  11. Park, S. H., Jin, M., & Kang, S. H. (2022). Efficient acceleration-level formula of bias acceleration satisfying time precedence for operational space formulation. IEEE Access, 10, 65533–65547. https://doi.org/10.1109/ACCESS.2022.3183609

    Article  Google Scholar 

  12. Yoshikawa, T. (1990). Foundations of robotics: Analysis and control. MIT Press.

    Google Scholar 

  13. Armstrong-Hélouvry, B., Dupont, P., & De Wit, C. C. (1994). A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica, 30(7), 1083–1138. https://doi.org/10.1016/0005-1098(94)90209-7

    Article  MATH  Google Scholar 

  14. Wit, CCd., Olsson, H., Astrom, K. J., & Lischinsky, P. (1995). A new model for control of systems with friction. IEEE Transactions on Automatic Control, 40(3), 419–425. https://doi.org/10.1109/9.376053

    Article  MathSciNet  MATH  Google Scholar 

  15. Liang, M., & Zhou, D. (2022). A nonlinear friction identification method combining separable least squares approach and kinematic orthogonal property. International Journal of Precision Engineering and Manufacturing, 23(2), 139–152. https://doi.org/10.1007/s12541-021-00611-0

    Article  Google Scholar 

  16. Schempf, H., & Yoerger, D. R. (1993). Study of dominant performance characteristics in robot transmissions. ASME Journal of Mechanical Design, 115(3), 472–482. https://doi.org/10.1115/1.2919214

    Article  Google Scholar 

  17. Mei, Z.-q, Xue, Y.-c, & Yang, R.-q. (2005). Nonlinear friction compensation in mechatronic servo systems. The International Journal of Advanced Manufacturing Technology, 30(7), 693. https://doi.org/10.1007/s00170-005-0113-y

    Article  Google Scholar 

  18. Bona, B., Indri, M., & Smaldone, N. (2006). Rapid prototyping of a model-based control with friction compensation for a direct-drive robot. IEEE/ASME Transactions on Mechatronics, 11(5), 576–584. https://doi.org/10.1109/TMECH.2006.882989

    Article  Google Scholar 

  19. Liu, G., Goldenberg, A. A., & Zhang, Y. (2004). Precise slow motion control of a direct-drive robot arm with velocity estimation and friction compensation. Mechatronics, 14(7), 821–834. https://doi.org/10.1016/j.mechatronics.2004.03.002

    Article  Google Scholar 

  20. Marton, L., & Lantos, B. (2007). Modeling, identification, and compensation of stick-slip friction. IEEE Transactions on Industrial Electronics, 54(1), 511–521. https://doi.org/10.1109/TIE.2006.888804

    Article  Google Scholar 

  21. Xie, W. F. (2007). Sliding-mode-observer-based adaptive control for servo actuator with friction. IEEE Transactions on Industrial Electronics, 54(3), 1517–1527. https://doi.org/10.1109/TIE.2007.894718

    Article  Google Scholar 

  22. Vukobratovic, M. (1989). Introduction to robotics. Springer.

    Book  Google Scholar 

  23. Valavanis, K. P., & Saridis, G. N. (1992). Intelligent robotic systems: Theory, design and applications. Springer.

    Book  MATH  Google Scholar 

  24. Gaidhane, P. J., Nigam, M. J., Kumar, A., & Pradhan, P. M. (2019). Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload. ISA Transactions, 89, 169–185. https://doi.org/10.1016/j.isatra.2018.12.030

    Article  Google Scholar 

  25. Lee, J., Chang, P. H., Yu, B., & Jin, M. (2020). An adaptive PID control for robot manipulators under substantial payload variations. IEEE Access, 8, 162261–162270. https://doi.org/10.1109/ACCESS.2020.3014348

    Article  Google Scholar 

  26. Morgan, R., & Ozguner, U. (1985). A decentralized variable structure control algorithm for robotic manipulators. IEEE Journal on Robotics and Automation, 1(1), 57–65. https://doi.org/10.1109/JRA.1985.1086998

    Article  Google Scholar 

  27. Hsia, T. C. S. (1989). A new technique for robust control of servo systems. IEEE Transactions on Industrial Electronics, 36(1), 1–7.

    Article  MathSciNet  Google Scholar 

  28. Hsia, T. C. S., & Gao, L. S. (1990). Robot manipulator control using decentralized linear time-invariant time-delayed joint controllers. In Proceedings of international conference on robotics and automation (pp. 2070–2075). IEEE.

  29. Hsia, T. C. S., Lasky, T. A., & Guo, Z. (1991). Robust independent joint controller design for industrial robot manipulators. IEEE Transactions on Industrial Electronics, 38(1), 21–25.

    Article  Google Scholar 

  30. Hsia, T. C. (1987). On a simplified joint controller design for robot manipulators. In 26th IEEE conference on decision and control (pp. 1024–1025). https://doi.org/10.1109/CDC.1987.272551

  31. Youcef-Toumi, K., & Ito, O. (1988). A time delay controller for systems with unknown dynamics. In Proceedings of American control conference (pp. 904–913).

  32. Youcef-Toumi, K., & Ito, O. (1990). A time delay controller for systems with unknown dynamics. ASME J Dyn Syst Meas Control, 112(1), 133–142.

    Article  MATH  Google Scholar 

  33. Youcef-Toumi, K., & Shortlidge, C. C. (1991). Control of robot manipulators using time delay. In IEEE international conference on robotics and automation (pp. 2391–2398). https://doi.org/10.1109/ROBOT.1991.131761

  34. Youcef-Toumi, K., & Wu, S.-T. (1992). Input/output linearization using time delay control. Journal of Dynamic Systems, Measurement, and Control, 114(1), 10–19. https://doi.org/10.1115/1.2896491

    Article  MATH  Google Scholar 

  35. Youcef-Toumi, K., & Ito, O. (1987). Controller design for systems with unknown nonlinear dynamics. In 1987 American control conference (pp. 836–845). https://doi.org/10.23919/ACC.1987.4789429

  36. Jin, M., Kang, S. H., & Chang, P. H. (2008). Robust compliant motion control of robot with nonlinear friction using time-delay estimation. IEEE Transactions on Industrial Electronics, 55(1), 258–269.

    Article  Google Scholar 

  37. Kang, S. H., Jin, M., & Chang, P. H. (2009). A solution to the accuracy/robustness dilemma in impedance control. IEEE/ASME Transactions on Mechatronics, 14(3), 282–294. https://doi.org/10.1109/TMECH.2008.2005524

    Article  Google Scholar 

  38. Jin, M., Kang, S. H., Chang, P. H., & Lee, J. (2017). Robust control of robot manipulators using inclusive and enhanced time delay control. IEEE/ASME Transactions on Mechatronics. https://doi.org/10.1109/TMECH.2017.2718108

    Article  Google Scholar 

  39. Hsia, T. C. S., & Jung, S. (1995). A simple alternative to neural network control scheme for robot manipulators. IEEE Transactions on Industrial Electronics, 42(4), 414–416.

    Article  Google Scholar 

  40. Youcef-Toumi, K., & Fuhlbrigge. T. A. (1989). Application of decentralized time-delay controller to robot manipulators. In Proceedings, 1989 international conference on robotics and automation (Vol. 1783, pp. 1786–1791). https://doi.org/10.1109/ROBOT.1989.100233

  41. Jin, M., Lee, J., Seo, K.-H., & Suh, J.-H. (2021). Self-tuning control for articulated robots using the Plestan’s method. International Journal of Precision Engineering and Manufacturing, 22(4), 557–566. https://doi.org/10.1007/s12541-021-00488-z

    Article  Google Scholar 

  42. Chang, P. H., Park, S.-H., & Lee, J.-H. (1999). A reduced order time-delay control for highly simplified brushless DC motor. Journal of Dynamic Systems, Measurement, and Control, 121(3), 556–560. https://doi.org/10.1115/1.2802514

    Article  Google Scholar 

  43. Chang, P. H., & Lee, J. W. (1994). An observer design for time-delay control and its application to DC servo motor. Control Engineering Practice, 2(2), 263–270. https://doi.org/10.1016/0967-0661(94)90206-2

    Article  Google Scholar 

  44. Park, J.-Y., & Chang, P.-H. (2004). Vibration control of a telescopic handler using time delay control and commandless input shaping technique. Control Engineering Practice, 12(6), 769–780. https://doi.org/10.1016/j.conengprac.2003.09.005

    Article  Google Scholar 

  45. Park, H.-S., Chang, P. H., & Lee, D. Y. (2003). Trajectory planning for the tracking control of systems with unstable zeros. Mechatronics, 13(2), 127–139. https://doi.org/10.1016/S0957-4158(01)00040-X

    Article  Google Scholar 

  46. Cho, G. R., Chang, P. H., & Jin, Y. (2010). Enhanced feedforward control of non-minimum phase systems for tracking predefined trajectory. In 2010 IEEE international symposium on industrial electronics (pp. 167–172). https://doi.org/10.1109/ISIE.2010.5637598

  47. Youcef-Toumi, K., & Reddy, S. (1992). Analysis of linear time invariant systems with time delay. Journal of Dynamic Systems, Measurement, and Control, 114(4), 544–555. https://doi.org/10.1115/1.2897722

    Article  MATH  Google Scholar 

  48. Choi, J. S., & Baek, Y. S. (2002). A single dof magnetic levitation system using time delay control and reduced-order observer. KSME International Journal, 16(12), 1643–1651. https://doi.org/10.1007/BF03021666

    Article  Google Scholar 

  49. Chang, P. H., & Park, S. H. (2003). On improving time-delay control under certain hard nonlinearities. Mechatronics, 13(4), 393–412.

    Article  Google Scholar 

  50. Six, K., Lasky, T. A., & Ravani, B. (2001). A time-delayed dynamic inversion scheme for mechatronic control of hydraulic systems. In 2001 IEEE/ASME international conference on advanced intelligent mechatronics. Proceedings (Cat. No.01TH8556) (Vol. 1232, pp. 1232–1238). https://doi.org/10.1109/AIM.2001.936888

  51. Kim, H-S., Kim, K.-H., & Youn, M.-J. (2003). On-line dead-time compensation method based on time delay control. IEEE Transactions on Control Systems Technology, 11(2), 279–285. https://doi.org/10.1109/TCST.2003.809251

    Article  Google Scholar 

  52. Kim, K-H., & Youn, M.-J. (2001). A simple and robust digital current control technique of a PM synchronous motor using time delay control approach. IEEE Transactions on Power Electronics, 16(1), 72–82. https://doi.org/10.1109/63.903991

    Article  Google Scholar 

  53. Ho-Seop, J., & Chong-Won, L. (1997). Time delay control with state feedback for azimuth motion of the frictionless positioning device. IEEE/ASME Transactions on Mechatronics, 2(3), 161–168. https://doi.org/10.1109/3516.622968

    Article  Google Scholar 

  54. Chin, S.-M., Lee, C.-O., & Chang, P. H. (1994). An experimental study on the position control of an electrohydraulic servo system using time delay control. Control Engineering Practice, 2(1), 41–48. https://doi.org/10.1016/0967-0661(94)90572-X

    Article  Google Scholar 

  55. Lee, J., Yoo, C., Park, Y.-S., Park, B., Lee, S.-J., Gweon, D.-G., & Chang, P.-H. (2012). An experimental study on time delay control of actuation system of tilt rotor unmanned aerial vehicle. Mechatronics, 22(2), 184–194. https://doi.org/10.1016/j.mechatronics.2012.01.005

    Article  Google Scholar 

  56. Cheng, C.-C., & Chen, C.-Y. (1996). Controller design for an overhead crane system with uncretainty. Control Engineering Practice, 4(5), 645–653. https://doi.org/10.1016/0967-0661(96)00046-9

    Article  Google Scholar 

  57. Chang, P. H., & Lee, S.-J. (2002). A straight-line motion tracking control of hydraulic excavator system. Mechatronics, 12(1), 119–138. https://doi.org/10.1016/S0957-4158(01)00014-9

    Article  Google Scholar 

  58. Song, J.-B., & Byun, K.-S. (1999). Throttle actuator control system for vehicle traction control. Mechatronics, 9(5), 477–495. https://doi.org/10.1016/S0957-4158(99)00010-0

    Article  Google Scholar 

  59. Lee, H. J., & Lee, J. J. (2004). Time delay control of a shape memory alloy actuator. Smart Materials and Structures, 13(1), 227.

    Article  Google Scholar 

  60. Lee, H. J., & Lee, J. J. (2004). Modeling and time delay control of shape memory alloy actuators. Advanced Robotics, 18(9), 881–903. https://doi.org/10.1163/1568553042225750

    Article  Google Scholar 

  61. Talole, S., Ghosh, A., & Phadke, S. (2006). Proportional navigation guidance using predictive and time delay control. Control Engineering Practice, 14(12), 1445–1453.

    Article  Google Scholar 

  62. Chang, P. H., & Park, J. (2001). A concurrent design of input shaping technique and a robust control for high-speed/high-precision control of a chip mounter. Control Engineering Practice, 9(12), 1279–1285. https://doi.org/10.1016/S0967-0661(01)00092-2

    Article  Google Scholar 

  63. González, J., Barrón, M. A., & Vargas-Villamil, F. (2002). New discrete controller for a class of chemical reactors. Industrial & Engineering Chemistry Research, 41(19), 4758–4764. https://doi.org/10.1021/ie010062d

    Article  Google Scholar 

  64. Chang, P. H., & Lee, J. W. (1996). A model reference observer for time-delay control and its application to robot trajectory control. IEEE Transactions on Control Systems Technology, 4(1), 2–10. https://doi.org/10.1109/87.481761

    Article  Google Scholar 

  65. Sai, H., Xu, Z., Li, Y., & Wang, K. (2021). Adaptive nonsingular fast terminal sliding mode impedance control for uncertainty robotic manipulators. International Journal of Precision Engineering and Manufacturing, 22(12), 1947–1961. https://doi.org/10.1007/s12541-021-00589-9

    Article  Google Scholar 

  66. Youcef-Toumi, K., & Wu, S. T. (1992). Robustness and stability analysis of time delay control. In 1992 American control conference (pp. 2691–2695). https://doi.org/10.23919/ACC.1992.4792631

  67. Youcef-Toumi, K., & Huang, S. Y. (1993). Analysis of a time delay controller based on convolutions. In 1993 American control conference (pp. 2582–2586). https://doi.org/10.23919/ACC.1993.4793360

  68. Lewis, F. L., Dawson, D. M., & Abdallah, C. T. (2003). Robot manipulator control: Theory and practice (2nd ed.). CRC Press.

    Book  Google Scholar 

  69. Craig, J. J. (2005). Introduction to robotics: Mechanics and control (3rd ed.). Pearson Prentice Hal.

    Google Scholar 

  70. Jung, J. H., Chang, P.-H., & Kwon, O.-S. (2004). A new stability analysis of time delay control for input/output linearizable plants. In Proceedings of the 2004 American control conference (Vol. 4976, pp. 4972–4979). https://doi.org/10.23919/ACC.2004.1384638

  71. Jung, J. H., Chang, P. H., & Kang, S. H. (2007). Stability analysis of discrete time delay control for nonlinear systems. In 2007 American control conference (pp. 5995–6002). https://doi.org/10.1109/ACC.2007.4282317

  72. Lee, J., Medrano-Cerda, G. A., & Jung, J. H. (2020). Stability analysis for time delay control of nonlinear systems in discrete-time domain with a standard discretisation method. Control Theory and Technology, 18(1), 92–106. https://doi.org/10.1007/s11768-020-9125-2

    Article  MathSciNet  MATH  Google Scholar 

  73. Lee, E., Chang, P.-H., Park, J., & Schrader, C. B. (2003). Hybrid impedance/time-delay control from free space to constrained motion. In Proceedings of the 2003 American control conference (Vol. 2133, pp. 2132–2137). https://doi.org/10.1109/ACC.2003.1243389

  74. Lee, E., Park, J., Loparo, K. A., Schrader, C. B., & Chang, P. H. (2003). Bang-bang impact control using hybrid impedance/time-delay control. IEEE/ASME Transactions on Mechatronics, 8(2), 272–277. https://doi.org/10.1109/TMECH.2003.812849

    Article  Google Scholar 

  75. Hwang, S., Park, S. H., Jin, M., & Kang, S. H. (2021). A robust control of robot manipulators for physical interaction: Stability analysis for the interaction with unknown environments. Intelligent Service Robotics, 14(3), 471–484. https://doi.org/10.1007/s11370-021-00370-x

    Article  Google Scholar 

  76. Chang, P. H., Lee, J. W., & Park, S. H. (1997). Time delay observer: A robust observer for nonlinear plants. Journal of Dynamic Systems, Measurement, and Control, 119(3), 521–527. https://doi.org/10.1115/1.2801288

    Article  MATH  Google Scholar 

  77. Park, S.-H., & Chang, P.-H. (2000). An enhanced time delay observer for nonlinear systems. Transactions on Control, Automation and Systems Engineering, 2(3), 149–156.

    Google Scholar 

  78. Lee, J. W., & Chang, P. H. (1999). Input/output linearization using time delay control and time delay observer. KSME International Journal, 13(7), 546–556. https://doi.org/10.1007/BF03186445

    Article  Google Scholar 

  79. Chang, P. H., & Jung, J. H. (2009). A systematic method for gain selection of robust PID control for nonlinear plants of second-order controller canonical form. IEEE Transactions on Control Systems Technology, 17(2), 473–483. https://doi.org/10.1109/TCST.2008.2000989

    Article  Google Scholar 

  80. Chang, P. H., Kim, D. S., & Park, K. C. (1995). Robust force/position control of a robot manipulator using time-delay control. Control Engineering Practice, 3(9), 1255–1264. https://doi.org/10.1016/0967-0661(95)00124-D

    Article  Google Scholar 

  81. Kang, S. H., Jin, M., & Chang, P. H. (2008). An IMC based enhancement of accuracy and robustness of impedance control. In 2008 IEEE international conference on robotics and automation (pp. 2623–2628). https://doi.org/10.1109/ROBOT.2008.4543608

  82. Chang, P. H., Park, B. S., & Park, K. C. (1996). An experimental study on improving hybrid position/force control of a robot using time delay control. Mechatronics, 6(8), 915–931. https://doi.org/10.1016/S0957-4158(96)00028-1

    Article  Google Scholar 

  83. Liu, Z., Liu, W., Wang, P., Li, Z., Xu, Y., Yang, X., & Shu, F. (2023). High-precision position tracking control of giant magnetostrictive actuators using fractional-order sliding mode control with inverse Prandtl–Ishlinskii compensator. International Journal of Precision Engineering and Manufacturing, 24(3), 379–393. https://doi.org/10.1007/s12541-022-00762-8

    Article  Google Scholar 

  84. Åström, K. J., & Hägglund, T. (1995). PID controllers: Theory, design, and tuning (2nd ed.). Instrument Society of America.

    Google Scholar 

  85. Somefun, O. A., Akingbade, K., & Dahunsi, F. (2021). The dilemma of PID tuning. Annual Reviews in Control, 52, 65–74. https://doi.org/10.1016/j.arcontrol.2021.05.002

    Article  MathSciNet  Google Scholar 

  86. Lin, P., Wu, Z., Fei, Z., & Sun, X. M. (2022). A generalized PID interpretation for high-order LADRC and cascade LADRC for servo systems. IEEE Transactions on Industrial Electronics, 69(5), 5207–5214. https://doi.org/10.1109/TIE.2021.3082058

    Article  Google Scholar 

  87. Muthusamy, P. K., Garratt, M., Pota, H., & Muthusamy, R. (2022). Real-time adaptive intelligent control system for quadcopter unmanned aerial vehicles with payload uncertainties. IEEE Transactions on Industrial Electronics, 69(2), 1641–1653. https://doi.org/10.1109/TIE.2021.3055170

    Article  Google Scholar 

  88. Lee, J. Y., Jin, M., & Chang, P. H. (2014). Variable PID gain tuning method using backstepping control with time-delay estimation and nonlinear damping. IEEE Transactions on Industrial Electronics, 61(12), 6975–6985. https://doi.org/10.1109/TIE.2014.2321353

    Article  Google Scholar 

  89. Khatib, O. (1987). A unified approach for motion and force control of robot manipulators: The operational space formulation. IEEE Journal on Robotics and Automation, 3(1), 43–53. https://doi.org/10.1109/JRA.1987.1087068

    Article  Google Scholar 

  90. Chang, P.-H., Park, K. C., & Lee, S. (2000). An extension to operational space for kinematically redundant manipulators: Kinematics and dynamics. IEEE Transactions on Robotics and Automation, 16(5), 592–596. https://doi.org/10.1109/70.880809

    Article  Google Scholar 

  91. Park, S. H., Jin, M., & Kang, S. H. (2022). Efficient acceleration-level formula of bias acceleration satisfying time precedence for operational space formulation. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3183609

    Article  Google Scholar 

  92. Chang, P. H., & Jeong, J. W. (2012). Enhanced operational space formulation for multiple tasks by using time-delay estimation. IEEE Transactions on Robotics, 28(4), 773–786. https://doi.org/10.1109/TRO.2012.2187397

    Article  Google Scholar 

  93. Sentis, L., & Khatib, O. (2004). Task-oriented control of humanoid robots through prioritization. In IEEE/RSJ international conference on humanoid robots (pp. 475–480).

  94. Khatib, O., Sentis, L., Park, J., & Warren, J. (2004). Whole-body dynamic behavior and control of human-like robots. International Journal of Humanoid Robotics, 01(01), 29–43. https://doi.org/10.1142/S0219843604000058

    Article  Google Scholar 

  95. Sentis, L., & Khatib, O. (2005). Synthesis of whole-body behaviors through hierarchical control of behavioral primitives. International Journal of Humanoid Robotics, 02(04), 505–518. https://doi.org/10.1142/s0219843605000594

    Article  Google Scholar 

  96. Sentis, L., & Khatib, O. (2004). Prioritized multi-objective dynamics and control of robots in human environments. In IEEE/RAS IEEE-RAS international conference on humanoid robots (pp. 764–780). https://doi.org/10.1109/ICHR.2004.1442684

  97. Jeong, H., & Lee, I. (2022). Optimization for Whole Body Reaching Motion Without Singularity. International Journal of Precision Engineering and Manufacturing, 23(6), 639–651. https://doi.org/10.1007/s12541-022-00623-4

    Article  Google Scholar 

  98. Yoo, J., Ryu, K., Back, J., & Park, I.-W. (2022). Advantages of vertical pelvic movement in bipedal gaits for increasing stride length and reducing actuator power requirements. International Journal of Precision Engineering and Manufacturing, 23(3), 291–303. https://doi.org/10.1007/s12541-021-00541-x

    Article  Google Scholar 

  99. Zhang, X., Kim, D., Bang, J., & Lee, J. (2021). Time delay compensation of a robotic arm based on multiple sensors for indirect teaching. International Journal of Precision Engineering and Manufacturing, 22(11), 1841–1851. https://doi.org/10.1007/s12541-021-00542-w

    Article  Google Scholar 

  100. Lee, H.-J., & Kim, J.-Y. (2021). Balance control strategy of biped walking robot SUBO-1 based on force-position hybrid control. International Journal of Precision Engineering and Manufacturing, 22(1), 161–175. https://doi.org/10.1007/s12541-020-00438-1

    Article  Google Scholar 

  101. Umeno, T., & Hori, Y. (1991). Robust speed control of DC servomotors using modern two degrees-of-freedom controller design. IEEE Transactions on Industrial Electronics, 38(5), 363–368. https://doi.org/10.1109/41.97556

    Article  Google Scholar 

  102. Ohnishi, K., Shibata, M., & Murakami, T. (1996). Motion control for advanced mechatronics. IEEE/ASME Transactions on Mechatronics, 1(1), 56–67. https://doi.org/10.1109/3516.491410

    Article  Google Scholar 

  103. Kwon, S., & Chung, W. K. (2003). A discrete-time design and analysis of perturbation observer for motion control applications. IEEE Transactions on Control Systems Technology, 11(3), 399–407. https://doi.org/10.1109/TCST.2003.810398

    Article  Google Scholar 

  104. Kwon, S., & Chung, W. K. (2002). Robust performance of the multiloop perturbation compensator. IEEE/ASME Transactions on Mechatronics, 7(2), 190–200. https://doi.org/10.1109/TMECH.2002.1011257

    Article  Google Scholar 

  105. Oh, Y., & Chung, W. K. (1999). Disturbance-observer-based motion control of redundant manipulators using inertially decoupled dynamics. IEEE/ASME Transactions on Mechatronics, 4(2), 133–146. https://doi.org/10.1109/3516.769540

    Article  Google Scholar 

  106. Murakami, T., Oda, N., Miyasaka, Y., & Ohnishi, K. (1995). A motion control strategy based on equivalent mass matrix in multidegree-of-freedom manipulator. IEEE Transactions on Industrial Electronics, 42(2), 123–130. https://doi.org/10.1109/41.370377

    Article  Google Scholar 

  107. Wen-Hua, C., Ballance, D. J., Gawthrop, P. J., & Reilly, J. O. (2000). A nonlinear disturbance observer for robotic manipulators. IEEE Transactions on Industrial Electronics, 47(4), 932–938. https://doi.org/10.1109/41.857974

    Article  Google Scholar 

  108. Mohammadi, A., Marquez, H. J., & Tavakoli, M. (2017). Nonlinear Disturbance observers: Design and applications to Euler? Lagrange systems. IEEE Control Systems Magazine, 37(4), 50–72. https://doi.org/10.1109/MCS.2017.2696760

    Article  MathSciNet  MATH  Google Scholar 

  109. Chen, W. H., Yang, J., Guo, L., & Li, S. (2016). Disturbance-observer-based control and related methods—An overview. IEEE Transactions on Industrial Electronics, 63(2), 1083–1095. https://doi.org/10.1109/TIE.2015.2478397

    Article  Google Scholar 

  110. Chen, Y.-C., Cai, Y.-R., Cheng, M.-Y., & Su, K.-H. (2023). Disturbance suppression and contour following accuracy improvement: An adaptive PI-type sliding mode nonlinear extended state observer approach. International Journal of Precision Engineering and Manufacturing, 24(3), 353–370. https://doi.org/10.1007/s12541-022-00754-8

    Article  Google Scholar 

  111. Yamato, S., Nakanishi, K., Suzuki, N., & Kakinuma, Y. (2021). Development of automatic chatter suppression system in parallel milling by real-time spindle speed control with observer-based chatter monitoring. International Journal of Precision Engineering and Manufacturing, 22(2), 227–240. https://doi.org/10.1007/s12541-021-00469-2

    Article  Google Scholar 

  112. Sariyildiz, E., Sekiguchi, H., Nozaki, T., Ugurlu, B., & Ohnishi, K. (2018). A stability analysis for the acceleration-based robust position control of robot manipulators via disturbance observer. IEEE/ASME Transactions on Mechatronics, 23(5), 2369–2378. https://doi.org/10.1109/TMECH.2018.2854844

    Article  Google Scholar 

  113. Jung, S., & Lee, J. W. (2021). Similarity analysis between a nonmodel-based disturbance observer and a time-delayed controller for robot manipulators in cartesian space. IEEE Access, 9, 122299–122307. https://doi.org/10.1109/ACCESS.2021.3109568

    Article  Google Scholar 

  114. Yun, L., Kiam Heong, A., & Chong, G. C. Y. (2006). Patents, software, and hardware for PID control: An overview and analysis of the current art. IEEE Contr Syst Mag, 26(1), 42–54. https://doi.org/10.1109/MCS.2006.1580153

    Article  Google Scholar 

  115. Baek, J., Cho, S., & Han, S. (2018). Practical time-delay control with adaptive gains for trajectory tracking of robot manipulators. IEEE Transactions on Industrial Electronics, 65(7), 5682–5692. https://doi.org/10.1109/TIE.2017.2782238

    Article  Google Scholar 

  116. Baek, J., Jin, M., & Han, S. (2016). A new adaptive sliding-mode control scheme for application to robot manipulators. IEEE Transactions on Industrial Electronics, 63(6), 3628–3637. https://doi.org/10.1109/TIE.2016.2522386

    Article  Google Scholar 

  117. Cho, S.-J., Jin, M., Kuc, T.-Y., & Lee, J. S. (2014). Stability guaranteed auto-tuning algorithm of a time-delay controller using a modified Nussbaum function. International Journal of Control, 87(9), 1926–1935. https://doi.org/10.1080/00207179.2014.895423

    Article  MathSciNet  MATH  Google Scholar 

  118. Jin, M., Lee, J., & Tsagarakis, N. G. (2017). Model-free robust adaptive control of humanoid robots with flexible joints. IEEE Transactions on Industrial Electronics, 64(2), 1706–1715. https://doi.org/10.1109/TIE.2016.2588461

    Article  Google Scholar 

  119. Lee, J., Chang, P. H., & Jin, M. (2020). An adaptive gain dynamics for time delay control improves accuracy and robustness to significant payload changes for robots. IEEE Transactions on Industrial Electronics, 67(4), 3076–3085.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by the Korea Medical Device Development Fund Grant funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (Project Number: RS-2020-KD000165), and in part by the Translational Research Program for Rehabilitation Robots, National Rehabilitation Center, Ministry of Health and Welfare, South Korea, under Grant NRCTR-EX22006.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea

    Jeongwoo Son, Hyunah Kang & Sang Hoon Kang

  2. Department of Physical Therapy and Rehabilitation Science, University of Maryland, Baltimore, MD, 21201, USA

    Sang Hoon Kang

Authors
  1. Jeongwoo Son
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hyunah Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sang Hoon Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sang Hoon Kang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This paper is an invited paper (Invited Review)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Son, J., Kang, H. & Kang, S.H. A Review on Robust Control of Robot Manipulators for Future Manufacturing. Int. J. Precis. Eng. Manuf. 24, 1083–1102 (2023). https://doi.org/10.1007/s12541-023-00812-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-023-00812-9

Keywords

Search

Navigation