Neural network-based sliding mode adaptive control for robot manipulators

This paper addresses the robust trajectory tracking problem for a robot manipulator in the presence of uncertainties and disturbances. First, a neural network-based sliding mode adaptive control (NNSMAC), which is a combination of sliding mode technique, neural network (NN) approximation and adaptive technique, is designed to ensure trajectory tracking by the robot manipulator. It is shown using the Lyapunov theory that the tracking error asymptotically converge to zero. However, the assumption on the availability of the robot manipulator dynamics is not always practical. So, an NN-based adaptive observer is designed to estimate the velocities of the links. Next, based on the observer, a neural network-based sliding mode adaptive output feedback control (NNSMAOFC) is designed. Then it is shown by the Lyapunov theory that the trajectory tracking errors, the observer estimation errors asymptotically converge to zero. The effectiveness of the designed NNSMAC, the NN-based adaptive observer and the NNSMAOFC is illustrated by simulations.

[1]  Frank L. Lewis,et al.  Neural network output feedback control of robot manipulators , 1999, IEEE Trans. Robotics Autom..

[2]  Shuzhi Sam Ge,et al.  Adaptive Neural Network Control of Robotic Manipulators , 1999, World Scientific Series in Robotics and Intelligent Systems.

[3]  Wu-Sheng Lu,et al.  A reduced-order adaptive velocity observer for manipulator control , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[4]  Frank L. Lewis,et al.  Multilayer neural-net robot controller with guaranteed tracking performance , 1996, IEEE Trans. Neural Networks.

[5]  Frank L. Lewis,et al.  Neural Network Control Of Robot Manipulators And Non-Linear Systems , 1998 .

[6]  Jean-Jacques E. Slotine,et al.  Tracking control of non-linear systems using sliding surfaces with application to robot manipulators , 1983 .

[7]  Ruben Alejandro Garrido Moctezuma,et al.  Proceedings of the American Control Conference , 2011 .

[8]  Zoe Doulgeri,et al.  Sliding regime of a nonlinear robust controller for robot manipulators , 1999 .

[9]  Rong-Jong Wai,et al.  Tracking control based on neural network strategy for robot manipulator , 2003, Neurocomputing.

[10]  Mark W. Spong,et al.  Adaptive motion control of rigid robots: a tutorial , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[11]  Ricardo O. Carelli,et al.  Neural networks for advanced control of robot manipulators , 2002, IEEE Trans. Neural Networks.

[12]  C. Abdallah,et al.  Survey of the Robust Control of Robots , 1990, 1990 American Control Conference.

[13]  Romeo Ortega,et al.  Adaptive motion control of rigid robots: a tutorial , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[14]  Richard Colbaugh,et al.  Adaptive tracking control of rigid manipulators using only position measurements , 1997, J. Field Robotics.

[15]  M. Kemal Ciliz,et al.  Adaptive control of robot manipulators with neural network based compensation of frictional uncertainties , 2005, Robotica.

[16]  Young-Bae Kim,et al.  International Conference on Control, Automation and Systems , 2007 .

[17]  Tao Zhang,et al.  Stable Adaptive Neural Network Control , 2001, The Springer International Series on Asian Studies in Computer and Information Science.

[18]  Fuchun Sun,et al.  Neural adaptive tracking controller for robot manipulators with unknown dynamics , 2000 .

[19]  Euntai Kim,et al.  Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic , 2004, IEEE Trans. Fuzzy Syst..

[20]  Frank L. Lewis,et al.  Deadzone compensation in motion control systems using neural networks , 2000, IEEE Trans. Autom. Control..

[21]  Chiharu Ishii,et al.  Robust model-following control for a robot manipulator , 1997 .

[22]  Sangchul Won,et al.  An adaptive disturbance observer for a two-link robot manipulator , 2008, 2008 International Conference on Control, Automation and Systems.

[23]  Alexander S. Poznyak,et al.  Adaptive control of two-link manipulator via dynamic neural network , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[24]  P. Dorato,et al.  Survey of robust control for rigid robots , 1991, IEEE Control Systems.

[25]  Jean-Jacques E. Slotine,et al.  Tracking control of nonlinear systems using sliding surfaces , 1983 .

[26]  F. Lewis,et al.  Neural Network Control of Robot Arms and Nonlinear Systems , 1997 .