A Novel Virtual Sensor for Estimating Robot Joint Total Friction Based on Total Momentum
Source abstract
Abstract
Robot joint friction is an important and complicated issue in improving robot control performance. In this paper, a virtual sensor based on the total generalized momentum concept is proposed to estimate the total friction torque, including both the motor-side and link-side friction, of robot joints without joint torque sensors. The proposed algorithm only requires a robot joint dynamics model and not a complex friction model dependent on factors such as time and velocity. By compensating for the estimated friction torque with a robot joint controller, the trajectory tracking performance of the controller, especially the velocity tracking performance, can be improved. To verify the effectiveness of the developed algorithm, 2-DOF planar manipulator simulations and single-joint system experiments are conducted. The simulation and experimental results show that the designed virtual sensor can effectively estimate the total joint friction disturbance and that the controller trajectory tracking performance is improved after observed friction compensation. However, the position tracking performance improvement of the controller is less than that for the velocity tracking performance improvement during the experiments. In addition, the velocity step response ability and velocity tracking performance of the controller are improved more at low velocities than that at high velocities in the experiments. The proposed algorithm has engineering and theoretical significance for estimating robot joint friction and improving the performance of robot joint controllers.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Hydraulic and Pneumatic Systems · Iterative Learning Control Systems · Robotic Mechanisms and Dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Robotics and System, School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150080, China
Funding
National Natural Science Foundation of China · National Key R&D Program of China
References (48)
Show source-provided references
1. Kolegain, K., Léonard, F., Chevret, S., Attar, A.B., and Abba, G. (2019). Robotic Friction Stir Welding Path Planning with Deflection Compensation Using B-Splines, Springer.10.1007/978-3-319-78963-7_34 ↗
2. Nonlinear friction modelling and compensation control of hysteresis phenomena for a pair of tendon-sheath actuated surgical robots10.1016/j.ymssp.2015.01.001 ↗
3. Ossadnik, D., Guadarrama-Olvera, J.R., Dean-Leon, E., and Cheng, G. (2018, January 6–9). Adaptive Friction Compensation for Humanoid Robots without Joint-Torque Sensors. Proceedings of the IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), Beijing, China.10.1109/HUMANOIDS.2018.8624965 ↗
4. Kermani, M.R., Wong, M., Patel, R.V., Moallem, M., and Ostojic, M. (May, January 26). Friction compensation in low and high-reversal-velocity manipulators. Proceedings of the IEEE International Conference on Robotics and Automation, New Orleans, LA, USA.
5. Miyasaka, M., Matheson, J., Lewis, A., and Hannaford, B. (October, January 28). Measurement of the cable-pulley coulomb and viscous friction for a cable-driven surgical robotic system. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.
6. Robust feedforward control of robotic arms with friction model uncertainty10.1016/j.robot.2015.03.008 ↗
7. Cherkasov, O.Y., Zarodnyuk, A.V., and Bugrov, D.I. (2016, January 4–8). Range maximization and brachistochrone problem with Coulomb friction, viscous drag and accelerating force. Proceedings of the 11th International Conference on Mathematical Problems in Engineering, Aerospace and Sciences, La Rochelle, France.10.1063/1.4972632 ↗
8. Guo, S., Xu, C., Xiao, N., Bao, X., Zhao, Y., Yang, C., and Shen, R. (2017, January 6–9). Cable-driven interventional operation robot with Stribeck friction feedforward compensation. Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA), Takamatsu, Japan.10.1109/ICMA.2017.8016088 ↗
9. Armstrong-Helouvry, B. (2012). Control of Machines with Friction, Springer Science & Business Media.
10. Dahl and lugre dynamic friction models—The analysis of selected properties10.1016/j.mechmachtheory.2013.10.009 ↗
11. A mindlin derived dahl friction model10.1016/j.mechmachtheory.2017.06.019 ↗
12. Review and comparison of dry friction force models10.1007/s11071-015-2485-3 ↗
13. Experimental measurements and bristle friction modeling of nonlinear hysteresis loops and harmonic generation in rock fractures10.1121/1.5014936 ↗
14. A continuous version of the LuGre friction model applied to the adaptive control of a pneumatic servo system10.1016/j.jfranklin.2016.06.003 ↗
15. Adaptive control of hydraulic actuators with lugre model based friction compensation10.1109/TIE.2015.2423660 ↗
16. A modified lugre friction model for an accurate prediction of friction force in the pure sliding regime10.1016/j.ijnonlinmec.2015.08.013 ↗
17. Simoni, L., Beschi, M., Legnani, G., and Visioli, A. (October, January 28). Friction modeling with temperature effects for industrial robot manipulators. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.
18. Modelling the temperature in joint friction of industrial manipulators Modelling the temperature in joint friction of industrial manipulators10.1017/S0263574717000509 ↗
19. Gao, L., Yuan, J., Han, Z., Wang, S., and Wang, N. (2017, January 24–28). A friction model with velocity, temperature and load torque effects for collaborative industrial robot joints. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.10.1109/IROS.2017.8206141 ↗
20. Global asymptotic stability of a PID control system with Coulomb friction10.1109/TAC.2017.2774443 ↗
21. Finite-time adaptive sliding mode force control for electro-hydraulic load simulator based on improved GMS friction model10.1016/j.ymssp.2017.09.009 ↗
22. Control of high-precision direct-drive mechatronic servos: Tracking control with adaptive friction estimation and compensation10.1016/j.mechatronics.2017.02.005 ↗
23. Extended State Observer based Sliding Mode Control of an Omnidirectional Mobile Robot with Friction Compensation10.1109/TIE.2019.2892678 ↗
24. Continuous Friction Feedforward Sliding Mode Controller for a TriMule Hybrid Robot10.1109/TMECH.2018.2853764 ↗
25. Bona, B., and Indri, M. (2005, January 12–15). Friction compensation in robotics: An overview. Proceedings of the 44th IEEE Conference on Decision and Control, Seville, Spain.
26. Adaptive parameter estimation and control design for robot manipulators with finite-time convergence10.1109/TIE.2018.2803773 ↗
27. Roveda, L., Pallucca, G., Pedrocchi, N., Braghin, F., and Tosatti, L.M. (2016, January 12–15). Cartesian tasks oriented friction compensation through a reinforcement learning approach. Proceedings of the IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Banff, AB, Canada.10.1109/AIM.2016.7576882 ↗
28. Colomé, A., Planells, A., and Torras, C. (2015, January 26–30). A friction-model-based framework for reinforcement learning of robotic tasks in non-rigid environments. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.10.1109/ICRA.2015.7139990 ↗
29. Chuei, R., Cao, Z., and Man, Z. (December, January 30). Friction compensator based repetitive control with application to a brushless DC servo motor. Proceedings of the International Conference on Advanced Mechatronic Systems (ICAMechS), Melbourne, Australia.
30. Contouring control for three-axis machine tools based on nonlinear friction compensation for lead screws10.1016/j.ijmachtools.2016.06.001 ↗
31. Improved position tracking performance of a pneumatic actuator using a fuzzy logic controller with velocity, system lag and friction compensation10.1007/s12555-015-0202-0 ↗
32. Control of piezoelectric friction dampers in smart base-isolated structures using self-tuning and adaptive fuzzy proportional–derivative controllers10.1177/1045389X16667561 ↗
33. A novel fuzzy logic correctional algorithm for traction control systems on uneven low-friction road conditions10.1080/00423114.2015.1012212 ↗
34. Composite learning robot control with friction compensation: A neural network-based approach10.1109/TIE.2018.2886763 ↗
35. Modeling the static friction in a robot joint by genetically optimized BP neural network10.1007/s10846-018-0796-6 ↗
36. End-effector force estimation for flexible-joint robots with global friction approximation using neural networks10.1109/TII.2018.2876724 ↗
37. Multi-axis MEMS force sensor for measuring friction components involved in dexterous micromanipulation: Design and optimization10.1504/IJNM.2015.071924 ↗
38. Joint torque sensor embedded in harmonic drive using order tracking method for robotic application10.1109/TMECH.2017.2694039 ↗
39. Collision detection and safe reaction algorithm for non-backdrivable manipulator with single force/torque sensor10.1007/s10846-017-0695-2 ↗
40. Le Tien, L., Albu-Schaffer, A., De Luca, A., and Hirzinger, G. (2008, January 22–26). Friction observer and compensation for control of robots with joint torque measurement. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France.10.1109/IROS.2008.4651049 ↗
41. Robust swing-up and balancing control using a nonlinear disturbance observer for the pendubot system with dynamic friction10.1109/TRO.2015.2402512 ↗
42. Passive Friction Compensation Using a Nonlinear Disturbance Observer for Flexible Joint Robots with Joint Torque Measurements10.15625/1813-9663/35/1/13147 ↗
43. Robot collisions: A survey on detection, isolation, and identification10.1109/TRO.2017.2723903 ↗
44. Sensorless collision detection based on friction model for a robot manipulator10.1007/s12541-016-0002-3 ↗
45. He, S., Ye, J., Li, Z., Li, S., Wu, G., and Wu, H. (2015, January 6–9). A momentum-based collision detection algorithm for industrial robots. Proceedings of the 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China.10.1109/ROBIO.2015.7418943 ↗
46. Sensorless torsion control of elastic-joint robots with hysteresis and friction10.1109/TIE.2015.2453415 ↗
47. Craig, J.J. (2009). Introduction to Robotics: Mechanics and Control, Pearson Education. [3rd ed.].
48. Siciliano, B., Sciavicco, L., Villani, L., and Oriolo, G. (2010). Robotics: Modelling, Planning and Control, Springer Science & Business Media.10.1007/978-1-84628-642-1 ↗