Model-based control of industrial manipulators: An experimental analysis

Model-based control techniques for industrial robotic manipulators were experimentally analyzed. The case study for the analysis was the first three joints of a PUMA-560. Development of an advanced control evaluation environment removed the computational restrictions of previous studies. The specific issues of: incomplete and/or asynchronous dynamic compensation, feedback paradigm selection, payload sensitivity, and drive systems effects were experimentally analyzed. Evaluation results clearly demonstrate that the performance improvement capability of model-based control is not restricted to research robots. A model-based controller with complete feedforward compensation and sliding mode feedback reduced the maximum tracking error by at least a factor of five when compared to feedback alone. End-effector payload invariant tracking only requires mass information. Tracking performance is not dependent on dynamic compensation at the servo rate. Evaluation results provide insight for adaptive control law design and a baseline to compare their performance against.

[1]  Malcolm Good,et al.  Dynamic Models for Control System Design of Integrated Robot and Drive Systems , 1985 .

[2]  M. B. Leahy,et al.  Multiple model-based control: development and initial evaluation , 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

[3]  George N. Saridis,et al.  The ral hierarchical control system , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[4]  Takeo Kanade,et al.  Real-time implementation and evaluation of the computed-torque scheme , 1989, IEEE Trans. Robotics Autom..

[5]  Takeo Kanade,et al.  Control of a Direct-Drive Arm , 1983 .

[6]  Christopher G. Atkeson,et al.  Experimental evaluation of feedforward and computed torque control , 1987, IEEE Trans. Robotics Autom..

[7]  M. B. Leahy,et al.  Industrial manipulator control with feedforward dynamic compensation , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[8]  Michael B. Leahy,et al.  Adaptive model-based neural network control , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[9]  Kostas J. Kyriakopoulos,et al.  Minimum jerk path generation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[10]  T.A. Lasky,et al.  Robust independent robot joint control: design and experimentation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[11]  M. B. Leahy,et al.  Multiple model-based control of robotic manipulators: theory and simulation , 1989, Proceedings. IEEE International Symposium on Intelligent Control 1989.

[12]  George N. Saridis,et al.  Compensation of Industrial Manipulator Dynamics , 1989, Int. J. Robotics Res..

[13]  Kimon P. Valavanis,et al.  Evaluation of dynamic models for PUMA robot control , 1989, IEEE Trans. Robotics Autom..

[14]  Homayoun Seraji,et al.  Decentralized adaptive control of manipulators: theory, simulation, and experimentation , 1989, IEEE Trans. Robotics Autom..

[15]  Z.S. Tumeh.  A direct method in discrete decentralized time-varying control of robot manipulators , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[16]  Donald T. Gavel,et al.  Decentralized adaptive control experiments with the PUMA robot arm , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[17]  M. B. Leahy,et al.  Experimental analysis of robot control: a performance standard for the PUMA-560 , 1989, Proceedings. IEEE International Symposium on Intelligent Control 1989.

[18]  Gary B. Lamont,et al.  Model-based control with quantitative feedback theory , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[19]  Pradeep K. Khosla,et al.  Choosing sampling rates for robot control , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[20]  Michael B. Leahy.  Dynamics based control of vertically articulated manipulators , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[21]  Takeo Kanade,et al.  Experimental Evaluation of Nonlinear Feedback and Feedforward Control Schemes for Manipulators , 1988, Int. J. Robotics Res..

[22]  Russell L. Andersson.  Computer architectures for robot control: a comparison and a new processor delivering 20 real MFLOPS , 1989, Proceedings, 1989 International Conference on Robotics and Automation.