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| Content Provider | Springer Nature Link |
|---|---|
| Author | Liaw, Der Cherng Huang, Jeng Tze |
| Copyright Year | 1998 |
| Abstract | In this paper, the issues of contact friction compensation for constrained robots are presented. The proposed design consists of two loops. The inner loop is for the inverse dynamics control which linearizes the system by canceling nonlinear dynamics, while the outer loop is for friction compensation. Although various models of friction have been proposed in many engineering applications, frictional force can be modeled by the Coulomb friction plus the viscous force. Based on such a model, an on-line genetic algorithm is proposed to learn the friction coefficients for friction model. The friction compensation control input is also implemented in terms of the friction coefficients to cancel the effect of unknown friction. By the guidance of the fitness function, the genetic learning algorithm searches for the best-fit value in a way like the natural surviving laws. Simulation results demonstrate that the proposed on-line genetic algorithm can achieve good friction compensation even under the conditions of measurement noise and system uncertainty. Moreover, the proposed control scheme is also found to be feasible for friction compensation of friction model with Stribeck effect and position-dependent friction model. |
| Starting Page | 331 |
| Ending Page | 349 |
| Page Count | 19 |
| File Format | |
| ISSN | 09210296 |
| Journal | Journal of Intelligent & Robotic Systems |
| Volume Number | 23 |
| Issue Number | 2-4 |
| e-ISSN | 15730409 |
| Language | English |
| Publisher | Kluwer Academic Publishers |
| Publisher Date | 1998-01-01 |
| Publisher Place | Dordrecht |
| Access Restriction | Subscribed |
| Subject Keyword | Artificial Intelligence (incl. Robotics) Mechanical Engineering Automation and Robotics Electronic and Computer Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software |
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