Neural network output feedback control of robot manipulators

A robust neural network output feedback scheme is developed for the motion control of robot manipulators without measuring joint velocities. A neural network observer is presented to estimate the joint velocities. It is shown that all the signals in a closed-loop system composed of a robot, an observer, and a controller is uniformly ultimately bounded. This amounts to a separation principle for the design of nonlinear dynamic trackers for robotic systems. The neural network weights in both the observer and the controller are tuned online, with no off-line learning phase required. No exact knowledge of the robot dynamics is required so that the neural network controller is model-free and so applicable to a class of nonlinear systems which have a similar structure to robot manipulators. Simulation results on 2-link robot manipulator are reported to show the performance of the proposed output feedback control scheme.

[1]  Frank L. Lewis,et al.  Control of Robot Manipulators , 1993 .

[2]  S. Nicosia,et al.  Robot control by using only joint position measurements , 1990 .

[3]  Wen-Hong Zhu,et al.  A variable structure robot control algorithm with an observer , 1992, IEEE Trans. Robotics Autom..

[4]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..

[5]  Henk Nijmeijer,et al.  A passivity approach to controller-observer design for robots , 1993, IEEE Trans. Robotics Autom..

[6]  C. C. Wit,et al.  Adaptive control of robot manipulators via velocity estimated feedback , 1992 .

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

[8]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[9]  Ser Yong Lim,et al.  Re-examining the Nicosia-Tomei robot observer-controller from a backstepping perspective , 1996, IEEE Trans. Control. Syst. Technol..

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

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

[12]  Peter J. Gawthrop,et al.  Neural networks for control systems - A survey , 1992, Autom..

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

[14]  Nader Sadegh,et al.  A perceptron network for functional identification and control of nonlinear systems , 1993, IEEE Trans. Neural Networks.

[15]  Frank L. Lewis,et al.  Neural net robot controller with guaranteed tracking performance , 1993, Proceedings of 8th IEEE International Symposium on Intelligent Control.