Jinglei Zhou


  1. [1] G. Feng, A new stable tracking control scheme for robotic manipulators, IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, 27(3), 1997, 510–516.
  2. [2] Z.H. Man, M. O’day, and X.H. Yu, A robust adaptive terminal sliding mode control for rigid robotic manipulators, Journal of Intelligent and Robotic Systems, 24(1), 1999, 23–42.
  3. [3] C. Ham, Z. Qu, and R. Johnson, Robust fuzzy control for robot manipulators, IEE Proceedings-Control Theory Applications, 147(2), 2000, 212–216.
  4. [4] R.L. Qi, W.J. Zhou, and T.J. Wang, An obstacle avoidance trajectory planning scheme for space manipulators based on genetic algorithm, Robot, 36(3), 2014, 263–270.
  5. [5] S.I. Han, K.S. Lee, M.G. Park, and J.M. Lee, Robust adaptive deadzone and friction compensation of robot manipulator using RWCMAC network, Journal of Mechanical Science and Technology, 25(6), 2011, 1583–1594.
  6. [6] T.L. Mai, Y.N. Wang, and T.Q. Ngo, Adaptive tracking control for robot manipulator using fuzzy wavelet neural networks, International Journal of Robotics and Automation, 30(1), 2015, 26–39.
  7. [7] K. Kherraz, M. Hamerlain, and N. Achour, Robust neurofuzzy sliding mode controller for a flexible robot manipulator, International Journal of Robotics and Automation, 30(1), 2015, 1–10.
  8. [8] D.E. Koditschek, Adaptive and learning systems (New York: Springer US, 1986).
  9. [9] J.V. Amerongen, Adaptive steering of ships-A mode reference approach, Automatica, 20(1), 1984, 3–14.
  10. [10] Z. Chen, B. Yao, and Q.F. Wang, Accurate motion control of linear motors with adaptive robust compensation of nonlinear electromagnetic field effect, IEEE/ASME Transaction on Mechatronic, 18(3), 2013, 1122–1129.
  11. [11] W. Li and X.D. Chen, Compensation of hysteresis in piezoelectric actuators without dynamics modeling, Sensors and Actuators A: Physical, 199(1), 2013, 89–97.
  12. [12] X.D. Chen and W. Li, A monolithic self-sensing precision stage: Design, modeling, calibration, and hysteresis compensation, IEEE/ASME Transactions on Mechatronics, 20(2), 2015, 812–823.
  13. [13] A.C. Elizalde and P. Goldsmith, Robust adaptive visual servoing of a robot arm, International Journal of Robotics and Automation, 30(4), 2015, 345–356.
  14. [14] L. Kanellakopoulos, P.V. Kokotovic, and A.S. Morse, Systematic design of adaptive controller for feedback linearizable systems, IEEE Transactions on Automatic Control, 36(11), 1991, 1241–1253.
  15. [15] M.M. Azimi and H.R. Koofigar, Adaptive fuzzy backstepping controller design for uncertain underactuated robotic systems, Nonlinear Dynamics, 79(2), 2015, 1457–1468.
  16. [16] Q. Li, F.C. Liu, and L.H. Liang, The application of adaptive backstepping sliding mode for hybrid humanoid robot arm trajectory tracking control, Advances in Mechanical Engineering, 2014(6), 2014, 9.
  17. [17] S.R. Li and H.C. Ma, Robust adaptive motion/force control for manipulators using backstepping, Journal of China University of Petroleum: Edition of Natural Science, 38(1), 2014, 172–176.
  18. [18] D.C. Theodoridis, Y.S. Boutalis, and M.A. Christodoulou, A new adaptive neuro-fuzzy controller for trajectory tracking of robot manipulators, International Journal of Robotics and Automation, 26(1), 2011, 64–75.
  19. [19] Y.J. Liu, L. Liu, and S.C. Tong, Adaptive neural network tracking design for a class of uncertain nonlinear discrete-time systems with dead-zone, Science China: Information Sciences, 57(3), 2014, 1–12.
  20. [20] M. Chen, W.H. Chen, and Q.X. Wu, Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems suing disturbance observer, Science China: Information Sciences, 57(1), 2014, 1–13.
  21. [21] S. Islam and P.X. Liu, Robust adaptive fuzzy output feedback control system for robot manipulators, IEEE/ASME Transactions on Mechatronics, 16(2), 2011, 288–296.
  22. [22] B.K. Yoo and W.C. Ham, Adaptive control of robot manipulator using fuzzy compensator, IEEE Transactions on Fuzzy Systems, 8(2), 2000, 186–199.
  23. [23] J.L. Zhou and W.H. Zhang, Robust control for robots based on linear state equation, Proc. 3rd Int. Conf. on Impulsive Dynamical Systems and Applications, Qingdao, China, 2006, 454–459.
  24. [24] J.L. Zhou and W.H. Zhang, Robust control for robot with friction, Chinese Journal of Mechanical Engineering, 43(9), 2007, 102–106.
  25. [25] F.C. Sun, Z.Q. Sun, and G. Feng, Design of adaptive sliding mode controller for robot manipulators, Proc. 5th IEEE Conf. on Fuzzy Systems, New Orleans, USA, 1996, 817–823.
  26. [26] C.W. Meng, H.T. Chen, and Y.J. Wang, Backstepping-based control scheme for robot, Journal of Tong Ji University, 28(4), 2000, 443–447.
  27. [27] W.D. Chen, D.Z. Tang, H.T. Wang, and H.R. Wang, Robust tracking control of robot manipulators using backstepping, Journal of System Simulation, 16(4), 2015, 837–838, 841.
  28. [28] Y.Y. Min and Y.G. Liu, Barbalat Lemma and its application in analysis of system stability, Journal of Shandong University: Engineering Science, 37(1), 2007, 51–55.
  29. [29] H.T. Liu and T. Zhang, Tracking control of industrial robot based on time delay estimation and robust H∞ control, Journal of South China University of Technology: Natural Science, 40(1), 2012, 77–81, 87.
  30. [30] Y. Feng, X H. Yu, and Z.H. Man, Non-singular terminal sliding mode control of rigid manipulators, Automatica, 38(12), 2002, 2159–2167.
  31. [31] J.L. Zhou, Adaptive fuzzy finite-time control for uncertain robotic manipulator, International Journal of Robotics and Automation, 32(2), 2017, 134–141.
  32. [32] A. Ishiguro, T. Furuhashi, S. Okuma, and Y. Uchikawa, A neural network compensator for uncertainties of robots manipulators, IEEE Transactions on Industrial Electronics, 39(6), 1992, 565–570.
  33. [33] L.Y. Wang, T.Y. Chai, and C.Y. Yang, Neural-network based contouring control for robotic manipulators in operational space, IEEE Transactions on Control Systems Technology, 20(4), 2012, 1073–1080.
  34. [34] L. Yu, S.M. Fei, J. Huang, and Y. Gao, Trajectory switching control of robotic manipulators based on RBF neural networks, Circuits, Systems, and Signal Processing, 33(4), 2014, 1119–1133.

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