Robustness of Hybrid Learning Acceleration Feedback Control Scheme in Flexible Manipulators

This paper describes a practical approach to design and develop a hybrid learning with acceleration feedback control (HLC) scheme for input tracking and end-point vibration suppression of flexible manipulator systems. Initially, a collocated proportionalderivative (PD) control scheme using hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate a further hybrid control scheme of the collocated PD control and iterative learning control with acceleration feedback using genetic algorithms (GAs) to optimize the learning parameters. Experimental results of the response of the manipulator with the control schemes are presented in the time and frequency domains. The performance of the HLC is assessed in terms of input tracking, level of vibration reduction at resonance modes and robustness with various payloads.

Authors:

• M. Z Md Zain
• M. O. Tokhi
• M. S. Alam

Keywords:

• Flexible manipulator
• iterative learning control
• vibration suppression.

References:

[1] Book WJ, Majette M., Controller design for flexile distributed
parameter mechanical arm via combined state-space and frequency
domain techniques. Transactions of ASME: Journal of Dynamic
Systems, Measurement and Control 1983; 105(4): 245-254.
[2] Arimoto S., Kawamura S., and Miyazaki F., Bettering operation of
robots by learning, Journal of Robotic Systems, 1984; 1(2):123-140.
[3] Craig J. J., Adaptive Control of Mechanical Manipulators, Addison-
Wesley Publishing Company, 1988.
[4] Horowitz R., Learning control of robot manipulators, Journal of
Dynamic Systems, Measurement, and Control, June 1993; 115: 402-411.
[5] Panzieri S. and Ulivi G., Disturbance rejection of iterative learning
control applied to trajectory tracking for a flexible manipulator. In
Proceedings of 3rd European Control Conference, ECC, September
1995, pages 2374-2379.
[6] Amann N., Owens D. H., and Rogers E., Iterative learning control for
discrete time systems with exponential rate of convergence. Technical
Report 95/14, Centre for Systems and Control Engineering, University
of Exeter, 1995.
[7] Gunnarsson S. and Norrlöf M. A short introduction to iterative learning
control. Technical Report LiTH-ISY-R-1926, Department of Electrical
Engineering, 1997.
[8] PMI Motion Technologies, General Application of Printed Motors,
(PMI Motion Technologies, New York), 1988.
[9] Electro-craft Corporation. DC Motor Speed Control Servo Systems,
(Electro-craft Corporation/Robbins and Mayers, Minnesota), 1985.
[10] Azad K. M., Analysis and design of control mechanisms for flexible
manipulator systems. PhD thesis, Department of Automatic Control
and Systems Engineering, The University of Sheffield, 1994.
[11] D. Garg, and M. Kumar, "Optimal Path Planning and Energy
Minimization via Genetic Algorithm Applied to Cooperating
Manipulators", Proceeding of ASME, Special Publication of
DSCD/ASME, Paper No. IMECE2001/DSC-24509, 2001.