Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-23T07:04:14.907Z Has data issue: false hasContentIssue false

Modeling and adaptive control of a flexible one-link manipulator

Published online by Cambridge University Press:  09 March 2009

Jian-Shiang Chen
Affiliation:
Department of Mechanical Engineering, The Ohio State University, Columbus, Ohio 43210 (U.S.A.)
Chia-Hsiang Menq
Affiliation:
Department of Mechanical Engineering, The Ohio State University, Columbus, Ohio 43210 (U.S.A.)

Summary

The dynamics modeling and payload adaptability of a light-weight flexible one-link manipulator are studied. Using the FEM (Finite-Element Method) model of a flexible manipulator, a lower order Linear Quadratic Gaussian compensator can provide satisfactory performance without controller/observer spillover. Moreover, the payload can be separated from the beam model, therefore, it is expected that the identification algorithm should have better robustness than the other schemes. The simulation results have shown that the proposed payload-adaptation synthesizer, which synthesizes a payload identifier and a nominal regulator/estimator interpolator to obtain a near-optimal compensator, has good adaptability with varying payload. And the resulting synthesizer also provides a near-optimal damping for this sensor-actuator noncolocated system.

Type
R&D Profile Section
Copyright
Copyright © Cambridge University Press 1990

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Gevarter, W.B., “Basic Relations for Control of Flexible VehicleJ. AIAA 8, No. 4, 666672 (04, 1970).CrossRefGoogle Scholar
2.Cannon, R.H. and Schmitz, E., “Initial Experiments on the Control of a Flexible ManipulatorInt. J. Robotics Research 3, 6275 (1984).CrossRefGoogle Scholar
3.Menq, C.-H. and Chen, J.-S., “Dynamic Modeling and Payload-adaptation Control of A Flexible ManipulatorProceedings of 1988 International Conference on Robotics and Automation448453 (Spring, 1988).CrossRefGoogle Scholar
4.Book, W.J., Maizza-Neto, O. and Whitney, D.E., “Feedback Control of Two Beam, Two Joint Systems With Distributed FlexibilityJ. Dynamic Systems, Measurement and Control 97, No. 4, 424431 (12, 1975).CrossRefGoogle Scholar
5.Hastings, G.G. and Book, W.J., “A Linear Dynamic Model for Flexible Robotic ManipulatorsIEEE Control System Magazine 87, No. 1, 6164 (02, 1987).CrossRefGoogle Scholar
6.Hastings, G.G. and Book, W.J., “Experiment in Optimal Control of A Flexible ArmProceedings of 1987 IEEE International Conference on Robotics and Automation10241029 (Spring, 1986).Google Scholar
7.Meldrum, D.R. and Balas, M.J., “Application of Model Reference Adaptive Control to a Flexible Remote Manipulator ArmProceedings of American Control Conference825832 (Summer, 1986).CrossRefGoogle Scholar
8.Oakley, C.M. and Cannon, R.H., “Initial Experiments on the Control of a Two-link Manipulator With a Very Flexible Forearm1988 American Control Conference,Atlanta, Ga9961002 (06 15–18, 1988).CrossRefGoogle Scholar
9.Bossche, E., Dugard, L. and Landau, I.D., “Modelling and Identification of a Flexible ArmProceedings of American Control Conference16111616 (Summer, 1986).Google Scholar
10.Kotnik, P.T., “Modeling and Control of a Flexible Manipulator System” M.S. Thesis (Department of Electrical Engineering, The Ohio State University 06, 1987).Google Scholar
11.Hastings, G.G. and Book, W.J., “Verification of a Linear Dynamic Model for Flexible ManipulatorsProceedings of American Control Conference728729 (Summer, 1985).Google Scholar
12.Bar-Kana, I., Kaufman, H. and Balas, M., “Model Reference Adaptive Control of Large Structural SystemsJ. Guidance 6, No. 2, 112118 (04, 1985).CrossRefGoogle Scholar
13.Rovner, D., and JrCannon, R.H., “Experiments Toward On-line Identification and Control of a Very Flexible One-link ManipulatorInt. J. Robotics Research 6, No. 4, 319 (Winter, 1987).CrossRefGoogle Scholar
14.Nelson, W.L. and Mitra, D., “Load Estimation and Load Adaptive Optimal Control for a Flexible Robot Arm1986 IEEE International Conference on Robotics and Automation206211 (Spring, 1986).Google Scholar
15.Nelson, W.L. and Mitra, D., “End Point Sensing and Load Adaptive Optimal Control for a Flexible Robotic Arm1985 IEEE Conference on Decision and Control14101415 (12, 1985).CrossRefGoogle Scholar
16.Landau, I.D., Adaptive Control—The Model Reference Approach (Marcel Dekker, New York, 1979).Google Scholar
17.JrBryson, A.E., “Some Connections between Modern and Classical Control ConceptsASME J. of Dynamic Systems, Meausrement and Control 101, 9198 (06 1979).CrossRefGoogle Scholar
18.Przemieniecki, J.S., Theory of Matrix Structure Analysis (McGraw Hill Book Company, New York, 1968) pp 328339.Google Scholar
19.Kwakernaak, K. and Sivan, R., Linear Optimal Control Systems, Chapter 3 and Chapter 4 (Wiley-Interscience, New York, 1972).Google Scholar
20.Popov, V.M., “the Solution of a new Stability Problem for Controlled SystemsAut. Remote Control 24, 123 (1963).Google Scholar
21.Goodwin, G.C. and Sin, K.S., Adaptive Filtering Prediction and Control (Prentice-Hall Inc., Englewood Cliffs, N.J., 1984).Google Scholar
22.Ljung, L. and Soderstrom, T., Theory and Practice of Recursive Identification (M.I.T. Press, Boston, Mass., 1983).Google Scholar
23.Parks, P.C., “Lyapunov Redesign of Model Reference Adaptive Control SystemIEEE Transactions on Automatic Conrrol AC-11, No. 3, 362367 (07, 1966).CrossRefGoogle Scholar
24.Mendel, J.M., Gradient Identification for Linear Systems, in Adaptive, Learning and Pattern Recognition Systems (Edited by Mendel, J.M. and Fu, K.S.) (Academic Press, New York, 1970).Google Scholar