JRM Vol.28 No.4 pp. 568-578
doi: 10.20965/jrm.2016.p0568


Operator-Based Robust Nonlinear Control Design of a Robot Arm with Micro-Hand

Zhengxiang Ma*, Aihui Wang**, and Tiejun Chen*

*School of Electric Engineering, Zhengzhou University
No.100, Science Road, Zhengzhou 450001, China

**School of Electric and Information Engineering, Zhongyuan University of Technology
41 Zhongyuan Road, Zhengzhou 450007, China

February 1, 2016
June 8, 2016
August 20, 2016
robot arm, micro-hand, robust right coprime factorization, robust control
This work focuses on a robust nonlinear control design of a robot arm with micro-hand (RAMH) by using operator-based robust right coprime factorization (RRCF) approach. In the proposed control system, we can control the endpoint position of robot arm and obtain the desired force of micro-hand to perform a task, and a miniature pneumatic curling soft (MPCS) actuator which can generate bidirectional curling motions in different positive and negative pressures is used to develop the fingers of micro-hand. In detail, to control successively the precise position of robot arm and the desired force of three fingers according to the external environment or task involved, this paper proposes a double-loop feedback control architecture using operator-based RRCF approach. First, the inner-loop feedback control scheme is designed to control the angular position of the robot arm, the operator controllers and the tracking controller are designed, and the robust stability and tracking conditions are derived. Second, the complex stable inner-loop and micro-hand with three fingers are viewed as two right factorizations separately, a robust control scheme using operator-based RRCF approach is presented to control the fingers forces, and the robust tracking conditions are also discussed. Finally, the effectiveness of the proposed control system is verified by experimental and simulation results.
Robot arm with micro-hand system

Robot arm with micro-hand system

Cite this article as:
Z. Ma, A. Wang, and T. Chen, “Operator-Based Robust Nonlinear Control Design of a Robot Arm with Micro-Hand,” J. Robot. Mechatron., Vol.28 No.4, pp. 568-578, 2016.
Data files:
  1. [1] S. Wittmeier, C. Alessandro, N. Bascarevic, K. Dalamagkidis, D. Devereus, A. Diamond, M. Jantsch, K. Jovanovic, R. Knight, H. G. Marques, P. Milosavljevic, B. Mitra, B. Svetozarevic, V. Potkonjak, R. Pfeifer, A. Knoll, and O. Holland, “Toward anthropomimetic robotics: development, simulation, and control of a musculoskeletal torso,” Artificial Life, Vol.19, No.1, pp. 171-193, 2014.
  2. [2] M. Yamashita, “Robotic rehabilitation system for human upper limbs using guide control and manipulability ellipsoid prediction,” Procedia Technology, Vol.15, pp. 560-566, 2014.
  3. [3] J. Zlotowski, D. Proudfoot, K. Yogeeswaran, and C. Bartneck, “Anthropomorphism: opportunities and challenges in human-robot interaction,” Int. J. Social Robotics, Vol.7, No.3, pp. 347-360, 2015.
  4. [4] H. Cha, K. Koh, and B. Yi, “Stiffness modeling of a soft finger,” Int. J. Control, Automation, and Systems, Vol.12, No.1, pp. 111-117, 2014.
  5. [5] F. Lewis, D. Dawson, and C. Abdallah, “Robot Manipulator Control: Theory and Practice,” Marcel Dekker, Inc., 2004.
  6. [6] K. Althoefer, B. Krekelberg, D. Husmeier, and L. Seneviratne, “Reinforcement learning in a rule-based navigator for robotic manipulators,” Neurocomputing, Vol.37, No.1-4, pp. 51-70, 2011.
  7. [7] C. Chiena and A. Tayebib, “Further results on adaptive iterative learning control of robot manipulators,” Automatica, Vol.44, No.3, pp. 830-837, 2008.
  8. [8] S. Islam and P. Liu, “Robust adaptive fuzzy output feedback control system for robot manipulators,” IEEE Trans. on Mechatronics, Vol.16, No.2, pp. 288-296, 2011.
  9. [9] H. Kang and J. Wang, “Adaptive robust control of 5 DOF upper-limb exoskeleton robot,” Int. J. Control, Automation, and Systems, Vol.13, No.3, pp. 733-741, 2015.
  10. [10] V. Arakelian, J. L. Baron, and P. Mottu, “Torque minimisation of the 2-DOF serial manipulators based on minimum energy consideration and optimum mass redistribution,” Mechatronics, Vol.21, No.1, pp. 310-314, 2011.
  11. [11] S. Devasia, “Nonlinear minimum-time control with pre- and post-actuation,” Automatica, Vol.47, No.7, pp. 1379-1387, 2011.
  12. [12] N. Kumara, V. Panwar, N. Sukavanam, S. P. Sharma, and J. H. Borm, “Neural network-based nonlinear tracking control of kinematically redundant robot manipulators,” Mathematical and Computer Modelling, Vol.53, No.9-10, pp. 1889-1901, 2011.
  13. [13] S. Islam and X. Liu, “Robust sliding mode control for robot manipulators,” IEEE Trans. on Industrial Electronics, Vol.58, No.6, pp. 2444-2453, 2011.
  14. [14] M. R. Soltanpour, P. Otadolajam, and M. H. Khooban, “Robust control strategy for electrically driven robot manipulators: adaptive fuzzy sliding mode,” IET Science, Measurement & Technology, Vol.9, No.3, pp. 322-334, 2015.
  15. [15] Z. Yang, Y. Fukushima, and P. Qin, “Decentralized adaptive robust control of robot manipulators using disturbance observers,” IEEE Trans. on Control Systems Technology, Vol.20, No.5, pp. 1357-1365, 2012.
  16. [16] Z. Chu, J. Cui, and F. Sun, “Fuzzy adaptive disturbance-observer-based robust tracking control of electrically driven free-floating space manipulator,” IEEE Systems J., Vol.8, No.2, pp. 343-352, 2014.
  17. [17] D. Sasaki, T. Noritsugu, and M. Takaiwa, “Development of pneumatic soft robot hand for human friendly robot,” J. of Robotics and Mechatronics, Vol.15, No.2, pp. 164-171, 2003.
  18. [18] G. Belforte, G. Eula, A. Ivanov, and S. Sirolli, “Soft pneumatic actuators for rehabilitation,” Actuators, Vol.3, pp. 84-106, 2014.
  19. [19] L. Bodenhagen, A. F. Fugl, A. Jordt, M. Willatzen, K. A. Andersen, and M. M.Olsen, “An adaptable robot vision system performing manipulation actions with flexible objects,” IEEE Trans. on Automation Science and Engineering, Vol.11, No.3, pp. 749-765, 2014.
  20. [20] C. Laschi and M. Cianchetti, “Soft robotics: new perspectives for robot bodyware and control,” Bioengineering and Biotechnology, doi:10.3389/fbioe.2014.00003, 2014.
  21. [21] K. Kawashima, T. Sasaki, T. Miyata, N. Nakamura, M. Sekiguchi, and T. Kagawa, “Development of robot using pneumatic artificial rubber muscles to operate construction machinery,” J. of Robotics and Mechatronics, Vol.16, No.1, pp. 8-16, 2004.
  22. [22] M. Deng, S. Bi, and A. Inoue, “Robust nonlinear control and tracking design for multi-input multi-output nonlinear perturbed plants,” IET Control Theory & Applications, Vol.3, No.9, pp. 1237-1248, 2009.
  23. [23] M. Deng, “Operator-based nonlinear control system design and applications,” Wiley-IEEE Press, New York, 2014.
  24. [24] A. Wang, D. Wang, H. Wang, S. Wen, and M. Deng, “Nonlinear perfect tracking control for a robot arm with uncertainties using operator-based robust right coprime factorization approach,” J. of Robotics and Mechatronics, Vol.27, No.1, pp. 49-56, 2015.
  25. [25] D. Wang, F. Li, X. Qi, P. Liu, and M. Deng, “Operator-based sliding-mode nonlinear control design for a process with input constraint,” J. of Robotics and Mechatronics, Vol.27, No.1, pp. 83-90, 2015.
  26. [26] A. Wang, M. Deng, and D. Wang, “Operator-based robust control design for a human arm-like manipulator with time-varying delay measurement,” Int. J. Control, Automation, and systems, Vol.11, No.6, pp. 1112-1121, 2013.
  27. [27] A. Wang, M. Deng, S. Wakimoto, and T. Kawashima, “Characteristics analysis and modeling of a miniature pneumatic curling rubber actuator,” Int. J. Innovative Computing, Information and Control, Vol.10, No.3, pp. 1029-1039, 2014.
  28. [28] T. Kawashima, A. Wang, S. Wakimoto, and M. Deng, “Sensorless nonlinear control for a miniature pneumatic curling rubber actuator using robust right coprime factorization and SVR estimation,” IEEJ Trans. Electronics, Information and Systems, Vol.133, No.10, pp. 1924-1929, 2013.
  29. [29] S. Wakimoto, K. Suzumori, and K. Ogura, “A miniature pneumatic curling rubber actuator generating bidirectional motion with one air-supply tube,” Advanced Robotics, Vol.25, No.9-10, pp. 1311-1330, 2011.
  30. [30] A. Wang, Y. Fu, L. Liu, and J. Xiao, “Robust tracking control design to nonlinear plants with perturbation using operator-based observers,” Proc. 2014 Int. Conf. Advanced Mechatronic Systems, pp. 17-22, 2014.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jun. 19, 2024