Experimental Verification of Adaptive Dominant Type Hybrid Adaptive and Learning Controller for Trajectory Tracking of Robot Manipulators
Munadi* and Tomohide Naniwa**
*Department of Mechanical Engineering, Diponegoro University, Tembalang, Semarang 50275, Indonesia
**Department of Human and Artificial Intelligent Systems, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan
This paper presents an experimental study to verify an adaptive dominant type hybrid adaptive and learning controller for acquiring an accurate trajectory tracking of periodic desired trajectory of robot manipulators. The proposed controller is developed based on combining the model-based adaptive control (MBAC), repetitive learning control (RLC) and proportionalderivative (PD) control in which the MBAC input becomes dominant than other inputs. Dominance of adaptive control input gives the advantage that the proposed controller could adjust the feed-forward motion control input immediately after changing the desired motion or load of the manipulator. In motion control law, the proposed controller uses only one vector to estimate the unknown dynamical parameters. It makes the proposed controller as a simpler hybrid adaptive and learning controller which does not need much computational power and also is easily be implemented for real applications of robot manipulators. The proposed controller is verified through experiments on a four-link small robot manipulator as representation of a scale robot manipulator to ensure this controller can be applied in the real applications of robot manipulators. The experimental results show the effectiveness of the proposed controller by indicating the position tracking error approaches to zero.
-  Q. Chen, H. Chen, Y. Wang, and P. Y. Woo, “Global Stability Analysis for Some Trajectory Tracking Control Schemes of Robotic Manipulators,” J. of Robotic Systems, Vol.18, No.2, pp. 69-75, 2001.
-  F. Reyes and A. Rosado, “Polynomial Family of PD-type Controllers for Robot Manipulators,” Control Engineering Practice, Vol.13, No.4, pp. 441-450, 2005.
-  J. J. Craig, P. Hsu, and S. S. Sastry, “Adaptive Control of Mechanical Manipulators,” Int. J. of Robotics Research, Vol.6, No.2, pp. 16-28, 1987.
-  J. J. E. Slotine and W. Li, “On The Adaptive Control of Robot Manipulators,” Int. J. of Robotics Research, Vol.6, No.3, pp. 49-59, 1987.
-  A. Cezayirli and K. Ciliz, “Multiple Model Based Adaptive Control of a DC Motor Under Load Changes,” Proc. of the IEEE Int. Conf. on Mechatronics, pp. 328-333, 2004.
-  M. C. Chien and A. C. Huang, “Adaptive Control of Electrically-Driven RobotWithout Computation of Regressor Matrix,” J. of Chinese Institute of Engineers, Vol.30, No.5, pp. 855-862, 2007.
-  S. Arimoto, S. Kawamura, and F.Miyazaki, “Bettering Operation of Robots by Learning,” J. of Robotic Systems, Vol.1, No.2, pp. 123-140, 1984.
-  R. Horowitz, “Learning Control of Robot Manipulators,” ASME J. of Dynamic Systems, Measurement, and Control, Vol.115, pp. 402-411, 1993.
-  W. W. Kao, R. Horowitz, M. Tomizuka, and M. Boals, “Repetitive Control of a Two Degree of Freedom SCARA Manipulators,” Proc. of the 1989 American Control Conf., pp. 1484-1490, 1989.
-  S. M. Xuan, H. X. Xiong, and C. B. Yu, “Repetitive Learning Control for Time-varying Robotic Systems: A Hybrid Learning Scheme,” Acta Automatica Sinica, Vol.33, No.11, pp. 1189-1195, 2007.
-  P. R. Ouyang,W. J. Zhang, and M.M. Gupta, “An Adaptive Switching Learning Control Method for Trajectory Tracking of Robot Manipulator,” Mechatronics, Vol.16, No.1, pp. 51-61, 2006.
-  C. J. Chien and A. Tayebi, “Further Results on Adaptive Iterative Learning Control of Robot Manipulators,” Automatica, Vol.44, No.3, pp. 830-837, 2008.
-  D. M. Dawson, R. Genet, and F. L. Lewis, “A Hybrid Adaptive/Learning Controller for a Robot Manipulator,” Proc. of Symposium on Adaptive and Learning Control ASME Winter Meeting, DSC-21, pp. 51-54, 1991.
-  K. Kaneko and R. Herowitz, “Repetitive and Adaptive Control of Robot Manipulators With Velocity Estimation,” IEEE Trans. on Robotics and Automation, Vol.13, No.2, pp. 204-217, 1997.
-  W. E. Dixon, E. Zergeroglu, D. M. Dawson, and B. T. Costic, “Repetitive Learning Control: A Lyapunov-Based Approach,” IEEE Trans. on System, Man, and Cybernetics, Part B: Cybernetics, Vol.32, No.4, pp. 538-544, 2002.
-  Z. Cao and G. F. Ledwich, “Adaptive Repetitive Control to Track Variable Periodic Signals With Fixed Sampling Rate,” IEEE/ASME Trans. on Mechatronics, Vol.7, No.3, pp. 378-384, 2002.
-  M. Sun, S. S. Ge, and I. M. Y. Mareels, “Adaptive Repetitive Learning Control of Robotic Manipulators Without The Requirement for Initial Repositioning,” IEEE Trans. on Robotics, Vol.22, No.3, pp. 563-568, 2006.
-  S. Nakada and T. Naniwa, “A Hybrid Controller of Adaptive and Learning Control for Robot Manipulators,” Trans. of the Society of Instrument and Control Engineers, Vol.42, No.3, pp. 275-280, 2006.
-  S. Nakada and T. Naniwa, “An Adaptive Learning Controller for Robot Manipulators in which Adaptation Rule is Dominant,” Proc. of 2007 CACS Int. Automatic Control Conf., D112, 2007.
-  M. Si and T. Naniwa, “Adaptation Dominant-Type Adaptive Learning Controller for Robot manipulators Using a Forgetting Factor,” Proc. of the 9th Int. IFAC Symposium on Robot Control, T3A3, 2009.
-  Munadi and T. Naniwa, “An Adaptive Controller Dominant-Type Hybrid Adaptive and Learning Controller for Trajectory Tracking of Robot Manipulators,” Advanced Robotics, Vol.26, pp. 45-61, 2013.
-  B. Bona and M. Indri, “Friction Compensation in Robotics: an Overview,” Proc. of the 44th IEEE Conf. on Decision and Control, and the European Control Conf. 2005, pp. 4360-4367, 2005.
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