Stable, online learning using CMACs for neuroadaptive tracking control of flexible-joint manipulators

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 1, Issue , 1998, Pages 511-517

  MacNab, C J B ^a   D'Eleuterio, G M T ^a  

^a UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATIVE PROCESSING; E-LEARNING; RADIAL BASIS FUNCTION NETWORKS; ROBOTICS; ROBOTS; ADAPTIVE CONTROL SYSTEMS; ALGORITHMS; ASSOCIATIVE STORAGE; INTELLIGENT CONTROL; LEARNING SYSTEMS; NEURAL NETWORKS; ONLINE SYSTEMS; SYSTEM STABILITY;

ASSOCIATIVE MEMORY; CEREBELLAR MODEL ARITHMETIC COMPUTERS; FLEXIBLE JOINT MANIPULATOR; FLEXIBLE JOINT ROBOTS; PRECISION CONTROL; RADIAL BASIS FUNCTIONS; TRACKING CONTROLS; TRAINING METHODS;

FLEXIBLE MANIPULATORS; MANIPULATORS;

CEREBELLAR MODEL ARITHMETIC COMPUTER (CMAC); FLEXIBLE JOINT MANIPULATORS; RADIAL BASIS FUNCTIONS;

EID: 0031640829     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.1998.677025     Document Type: Conference Paper

References (17)

1. Albus J., A new approach to manipulator control: The cerebellar model articulation controller (CMAC). J. Dyn. Sys. Meas. Contr, Vol. 97, pp. 220-227, 1975.
2. Albus J., Data storage in the cerebellar model articulation controller (CMAC). J. Dyn. Sys. Meas. Contr, vol. 97, pp. 228-233, 1975.
3. Bortoff, S.A., Spong, M.W., Feedback linearization of flexible joint manipulators. Proc. IEEE Conf. Decision and Control. 1357-1362, 1987.
4. Brogliato, B., Ortega, R., Lozano, R., Global tracking controllers for flexible-joint manipulators: A comparative study. Automatica, vol. 31, no. 7, pp. 941-956, 1995.
5. Commuri, S., Lewis, F.L., CMAC neural networks for control of nonlinear dynamical systems: Structure, stability, and passivity. Automatica, vol. 33, no. 4, pp. 635-641, 1997.
6. Fabri, S., Kadirkamanathan, V., Dynamic Structure Neural Networks for Stable Adaptive Control of Nonlinear Systems. IEEE Trans. Neural Networks, vol. 7, no. 5, pp. 1151-1167, 1996.
7. Graham, RW., D'Eleuterio, G.M.T., A neural network paradigm for robotic control, Can. Aero. Space J. vol. 37, no. l, pp. 17-26, 1991.
8. Ioannou, P.A., Robust Adaptive Control, Prentice-Hall, Upper Saddle River, NJ, 1996.
9. Krstic, M., Kanellakopoulos, I., Kokotovic, P., Nonlinear Adaptive Control Design, Wi\ey, New York, 1995.
10. Kwan, CM., Lewis, F.L., Kim, Y.H., Robust neural network control of flexible-joint robots. Proc. 34th Conf. Decision and Control, (New Orleans ), pp. 1296-1301, 1995.
11. Miller, Thomas W., Sensor-based control of robotic manipulators using a general learning algorithm. J. Robot. Autom, vol. RA-3, no. 2, pp. 157-165, 1987.
12. Narendra, N.S., Annaswamy, A.M., Robust adaptive control in the presence of bounded disturbances. IEEE Trans. Aut. Control, vol. AC-31, pp. 306-315, 1986.
13. Narendra, N.S., Annaswamy, A.M., A new adaptive law for robust adaptive control without persistence of excitation. IEEE Trans. Aut. Control, vol. AC-32, pp. 134-135, 1987.
14. Narendra, K.S., Annaswamy, A.M. Stable Adaptive Systems, Englewood Cliffs, NJ: Prentic-Hall, 1989.
15. Nicosia, S., Tomei, P., A method to design adaptive controllers for flexible joint robots. Proc. IEEE Int. Conf. Robotics and Automation, (Nice, France), pp. 701-706, 1992.
16. Qu, Z., Dawson, D.M., Robust Tracking Control of Robot Manipulators, IEEE Press, New York, 1996.
17. Spong, M.W., Vidyasagar, M., Robot Dynamics and Control, John Wiley and Sons, New York, 1989.