Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
169 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Sliding Mode Control for 3-D Uncalibrated and Constrained Vision-based Shape Servoing within Input Saturation (2312.16048v1)

Published 26 Dec 2023 in cs.RO

Abstract: This paper designs a servo control system based on sliding mode control for the shape control of elastic objects. In order to solve the effect of non-smooth and asymmetric control saturation, a Gaussian-based continuous differentiable asymmetric saturation function is used for this goal. The proposed detection approach runs in a highly real-time manner. Meanwhile, this paper uses sliding mode control to prove that the estimation stability of the deformation Jacobian matrix and the system stability of the controller are combined, which verifies the control stability of the closed-loop system including estimation. Besides, an integral sliding mode function is designed to avoid the need for second-order derivatives of variables, which enhances the robustness of the system in actual situations. Finally, the Lyapunov theory is used to prove the consistent final boundedness of all variables of the system.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (30)
  1. T. Grützner, H. Hasse, N. Lang, M. Siegert, and E. Ströfer, “Development of a new industrial process for trioxane production,” Chemical Engineering Science, vol. 62, no. 18-20, pp. 5613–5620, 2007.
  2. D. Gerhardus, “Robot-assisted surgery: the future is here,” Journal of Healthcare Management, vol. 48, no. 4, p. 242, 2003.
  3. M. Söderlund, “The robot-to-robot service encounter: an examination of the impact of inter-robot warmth,” Journal of Services Marketing, vol. 35, no. 9, pp. 15–27, 2021.
  4. V. N. Dubey and J. S. Dai, “A packaging robot for complex cartons,” Industrial Robot: An International Journal, vol. 33, no. 2, pp. 82–87, 2006.
  5. G. Ma, J. Qi, Y. Lv, and H. Zeng, “Active manipulation of elastic rods using optimization-based shape perception and sensorimotor model approximation,” in 2022 41st Chinese Control Conference (CCC).   IEEE, 2022, pp. 3780–3785.
  6. S. Zou, Y. Lyu, J. Qi, G. Ma, and Y. Guo, “A deep neural network approach for accurate 3d shape estimation of soft manipulator with vision correction,” Sensors and Actuators A: Physical, vol. 344, p. 113692, 2022.
  7. Z. Zheng and L. Sun, “Path following control for marine surface vessel with uncertainties and input saturation,” Neurocomputing, vol. 177, pp. 158–167, 2016.
  8. Y. Yu, H.-K. Lam, and K. Y. Chan, “T–s fuzzy-model-based output feedback tracking control with control input saturation,” IEEE Transactions on Fuzzy Systems, vol. 26, no. 6, pp. 3514–3523, 2018.
  9. D. Sheng, Y. Wei, S. Cheng, and J. Shuai, “Adaptive backstepping control for fractional order systems with input saturation,” Journal of the Franklin Institute, vol. 354, no. 5, pp. 2245–2268, 2017.
  10. J. Qi, G. Ma, J. Zhu, P. Zhou, et al., “Contour moments based manipulation of composite rigid-deformable objects with finite time model estimation and shape/position control,” IEEE/ASME Transactions on Mechatronics, vol. 27, no. 5, pp. 2985–2996, 2021.
  11. J. Sanchez, K. Mohy El Dine, J. A. Corrales, B.-C. Bouzgarrou, and Y. Mezouar, “Blind manipulation of deformable objects based on force sensing and finite element modeling,” Frontiers in Robotics and AI, vol. 7, p. 73, 2020.
  12. S. Tarbouriech and M. Turner, “Anti-windup design: an overview of some recent advances and open problems,” IET control theory & applications, vol. 3, no. 1, pp. 1–19, 2009.
  13. S. Mohammad-Hoseini, M. Farrokhi, and A. Koshkouei, “Robust adaptive control of uncertain non-linear systems using neural networks,” International Journal of control, vol. 81, no. 8, pp. 1319–1330, 2008.
  14. J. Qi, Y. Lv, D. Gao, Z. Zhang, and C. Li, “Trajectory tracking strategy of quadrotor with output delay,” in 2018 Eighth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC).   IEEE, 2018, pp. 1303–1308.
  15. S. Zhang, X. Qiu, and C. Liu, “Neural adaptive compensation control for a class of mimo uncertain nonlinear systems with actuator failures,” Circuits, Systems, and Signal Processing, vol. 33, pp. 1971–1984, 2014.
  16. H. Fallah Ghavidel and A. Akbarzadeh Kalat, “Observer-based hybrid adaptive fuzzy control for affine and nonaffine uncertain nonlinear systems,” Neural Computing and Applications, vol. 30, pp. 1187–1202, 2018.
  17. S. Gao, Y. Jing, X. Liu, and G. M. Dimirovski, “Chebyshev neural network-based attitude-tracking control for rigid spacecraft with finite-time convergence,” International Journal of Control, vol. 94, no. 10, pp. 2712–2729, 2021.
  18. A. Visioli, “Anti-windup strategies,” Practical PID control, pp. 35–60, 2006.
  19. M. Schiavo, F. Padula, N. Latronico, M. Paltenghi, and A. Visioli, “Individualized pid tuning for maintenance of general anesthesia with propofol and remifentanil coadministration,” Journal of Process Control, vol. 109, pp. 74–82, 2022.
  20. J. S. Lee et al., “Study of noise-induced tracking error phenomenon in systems with anti-windups,” Ph.D. dissertation, Daegu, 2015.
  21. M. Schiavo, L. Consolini, M. Laurini, N. Latronico, et al., “Optimized robust combined feedforward/feedback control of propofol for induction of hypnosis in general anesthesia,” in 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).   IEEE, 2021, pp. 1266–1271.
  22. M. A. Rodrigues and D. Odloak, “Robust mpc for systems with output feedback and input saturation,” Journal of Process Control, vol. 15, no. 7, pp. 837–846, 2005.
  23. G. Galuppini, L. Magni, and D. M. Raimondo, “Model predictive control of systems with deadzone and saturation,” Control Engineering Practice, vol. 78, pp. 56–64, 2018.
  24. T. Shi and H. Su, “Sampled-data mpc for lpv systems with input saturation,” IET Control Theory & Applications, vol. 8, no. 17, pp. 1781–1788, 2014.
  25. T. Hu, A. N. Pitsillides, and Z. Lin, “Null controllability and stabilization of linear systems subject to asymmetric actuator saturation,” in Proceedings of the 39th IEEE conference on decision and control (Cat. No. 00CH37187), vol. 4.   IEEE, 2000, pp. 3254–3259.
  26. C. Yuan and F. Wu, “A switching control approach for linear systems subject to asymmetric actuator saturation,” in Proceedings of the 33rd Chinese Control Conference.   IEEE, 2014, pp. 3959–3964.
  27. J. Qi, D. Li, Y. Gao, P. Zhou, and D. Navarro-Alarcon, “Model predictive manipulation of compliant objects with multi-objective optimizer and adversarial network for occlusion compensation,” arXiv preprint arXiv:2205.09987, 2022.
  28. M. M. Polycarpou and P. A. Ioannou, “A robust adaptive nonlinear control design,” in 1993 American control conference.   IEEE, 1993, pp. 1365–1369.
  29. J. Ma, S. S. Ge, Z. Zheng, and D. Hu, “Adaptive nn control of a class of nonlinear systems with asymmetric saturation actuators,” IEEE transactions on neural networks and learning systems, vol. 26, no. 7, pp. 1532–1538, 2014.
  30. Q. Shen, D. Wang, S. Zhu, and E. K. Poh, “Integral-type sliding mode fault-tolerant control for attitude stabilization of spacecraft,” IEEE Transactions on Control Systems Technology, vol. 23, no. 3, pp. 1131–1138, 2014.

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now