DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

An Adaptive Control Approach with Automatic Gain Blending for Robot Manipulators under Dynamic Uncertainties

Kirner, Annika (2021) An Adaptive Control Approach with Automatic Gain Blending for Robot Manipulators under Dynamic Uncertainties. DLR-Interner Bericht. DLR-IB-RM-OP-2021-219. Master's. Technical University of Munich.

[img] PDF - Only accessible within DLR


To ensure convergence of the tracking errors despite uncertainties in the inertial parameters of a robot manipulator, adaptive tracking controllers can be applied, which adapt a parameter estimate on-line. The common adaptive robot controllers feature a proportional-derivative (PD) feedback of the tracking errors. Tuning the PD gains can be challenging due to tradeoffs between desired control performance and the risk of exceeding feasible limits of actuators. Far from the desired equilibria, small gains are beneficial in order to avoid actuator saturation. However, low gains usually come at the cost of a degraded tracking performance, especially in the presence of model uncertainties. The thesis addresses the problem in proposing a combined adaptive tracking controller for robot manipulators. It adapts a parameter estimate utilizing a natural adaptation law. Moreover, nominal high gains and global low gains are adaptively blended depending on the current tracking errors and the estimated uncertainties. In general, the blended gains decrease with growing tracking errors. However, they are shifted towards the nominal high gains if the errors remain large or if model uncertainties are estimated to affect the control performance. Consequently, the current weighting between ensuring a desired control performance and avoiding large actuation effort is automatically adapted. A recently proposed adaptation mechanism that can blend two control actions depending on the current tracking errors is taken as a starting point for the controller development. The thesis extends the approach such that the current estimated uncertainties can be included and unifies it with a parameter adaptation law to obtain a combined adaptive controller. A mathematical proof for the global uniform convergence of the tracking errors and the boundedness of the parameter estimation error is provided. Simulative and experimental results with a lightweight robot manipulator with seven degrees of freedom validate the theoretic results.

Item URL in elib:https://elib.dlr.de/146748/
Document Type:Monograph (DLR-Interner Bericht, Master's)
Title:An Adaptive Control Approach with Automatic Gain Blending for Robot Manipulators under Dynamic Uncertainties
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Adaptive Control, Automatic Gain Blending, Natural Adaptation Law
Institution:Technical University of Munich
Department:TUM School of Engineering and Design - Chair of Automatic Control
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Robot Dynamics & Simulation [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Analysis and Control of Advanced Robotic Systems
Deposited By: Wu, Xuwei
Deposited On:06 Dec 2021 11:10
Last Modified:06 Dec 2021 11:10

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.