Neuro-Adaptive Friction Compensation for Single-Link Flexible Robots Using Serial-Gray-Box Modeling Strategy

[+] Author and Article Information
Ali Bazaei

Electrical Engineering Department, Tarbiat Modarres University, P. O. Box 14115-143, Tehran, Iran

Vahid Johari Majd1

Electrical Engineering Department, Tarbiat Modarres University, P. O. Box 14115-143, Tehran, Iranmajd@modares.ac.ir


Corresponding author.

J. Dyn. Sys., Meas., Control 128(2), 297-306 (Apr 27, 2005) (10 pages) doi:10.1115/1.2192838 History: Received October 27, 2003; Revised April 27, 2005

In this paper a previously offered black-box filtered-error neural-approximation-based control method for singularly perturbed flexible-link arms (FLA) is extended to a serial-gray-box method that assumes only the friction torques as unknown functions. Unlike the former method the knowledge of the unknown part is not used in design implementation of the fast control component. Because the neural network weights are updated adaptively the gray-box friction compensation method is applicable even when the friction functions change with time. Moreover, due to incorporation of the available first-principles knowledge into the control law the method exhibits dimensional extrapolation property with respect to nonfrictional measurable parameters of the plant. The capability of the gray-box method in the presence of static friction unmodeled dynamics are examined. Simulation results show that the proposed gray-box-based method provides better control modeling performances with less number of integrators in comparison with the black-box-based method. A procedure for determination of the parameters of the distributed mass-spring model is offered closed-form exact solutions for the equivalent deflection angle the spring coefficient the slope of the flexible-mode friction characteristic are derived. The gray-box method also works better than a newly developed Lyapunov-type controller which can be regarded as a robust control schema.

Copyright © 2006 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.



Grahic Jump Location
Figure 1

Structure of the simplified model of a single-link FLA

Grahic Jump Location
Figure 2

Simple friction models for (a) the hub (rigid mode friction), and (b) the second joint (flexible mode friction)

Grahic Jump Location
Figure 3

Structure of the neuro-gray-box friction compensator

Grahic Jump Location
Figure 4

Gray-box (GB) and black-box (BB) results

Grahic Jump Location
Figure 5

Black-box (BB) and gray-box (GB) tracking performance after (a) change in Tip-load, and (b) change in hub-friction

Grahic Jump Location
Figure 6

Three-beam model structure considered as actual FLA used to verify the two-beam model-based control

Grahic Jump Location
Figure 7

Unit-step responses of the actual arm and the two-beam model in the absence of frictions

Grahic Jump Location
Figure 8

Comparison of neuro-gray-box and Lyapunov-type controllers in the presence of unmodeled dynamics




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In