Intelligent control of robotic manipulators: a multiple model based approach

The paper presents a novel methodology for the trajectory tracking control of robotic manipulators. The proposed method utilizes multiple models of the manipulator for the identification of its dynamics in an adaptive control frame work. Simulations and experimental test results are also included to demonstrate the improvement in the tracking performance when the proposed methodology is used for different tracking tasks.

[1]  S. T. Venkataraman,et al.  Adaptation and learning in robotics and automation , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[2]  Kumpati S. Narendra,et al.  Improving transient response of adaptive control systems using multiple models and switching , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[3]  Kumpati S. Narendra,et al.  Adaptation and learning using multiple models, switching, and tuning , 1995 .

[4]  Roberto Horowitz,et al.  Stability analysis of an adaptive controller for robotic manipulators , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[5]  Kumpati S. Narendra,et al.  Multiple model based adaptive control of robotic manipulators , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[6]  Kumpati S. Narendra,et al.  Intelligent control using fixed and adaptive models , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.

[7]  K.S. Narendra,et al.  Intelligent control using neural networks , 1992, IEEE Control Systems.

[8]  Weiping Li,et al.  Composite adaptive control of robot manipulators , 1989, Autom..

[9]  J. Slotine,et al.  On the Adaptive Control of Robot Manipulators , 1987 .

[10]  Kumpati S. Narendra,et al.  Adaptive Control of Robotic Manipulators Using Multiple Models and Switching , 1996, Int. J. Robotics Res..

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