Nedelchev, S;
Kozlov, L;
Khusainov, R;
Gaponov, I;
(2024)
Enhanced Adaptive Control over Robotic Systems via Generalized Momentum Dynamic Extensions.
Russian Journal of Nonlinear Dynamics
, 19
(4)
pp. 633-646.
10.20537/nd231212.
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Abstract
Adaptive control and parameter estimation have been widely employed in robotics to deal with parametric uncertainty. However, these techniques may suffer from parameter drift, dependence on acceleration estimates and conservative requirements for system excitation. To overcome these limitations, composite adaptation laws can be used. In this paper, we propose an enhanced composite adaptive control approach for robotic systems that exploits the accelerationfree momentum dynamics and regressor extensions to offer faster parameter and tracking convergence while relaxing excitation conditions and providing a clear physical interpretation. The effectiveness of the proposed approach is validated through experimental evaluation on a 3-DoF robotic leg.
| Type: | Article |
|---|---|
| Title: | Enhanced Adaptive Control over Robotic Systems via Generalized Momentum Dynamic Extensions |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.20537/nd231212 |
| Publisher version: | http://dx.doi.org/10.20537/nd231212 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License. See: http://creativecommons.org/licenses/by-nd/3.0/ |
| Keywords: | Adaptive control, parameter estimation, motion control |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10187443 |
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