Identification of Linearized Joint Model and Acceleration of a Robot Manipulator by RLS Algorithm and State Observer
| Autor: | Seul Jung, Sang D. Lee |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Recursive least squares filter
0209 industrial biotechnology Computer science media_common.quotation_subject 020208 electrical & electronic engineering System identification 02 engineering and technology Inertia Signal Data-driven Acceleration 020901 industrial engineering & automation Control theory 0202 electrical engineering electronic engineering information engineering Torque State observer media_common |
| Zdroj: | 2019 19th International Conference on Control, Automation and Systems (ICCAS). |
| Popis: | The time-delayed control (TDC) requires the inertia model and acceleration signals as well as the previous torque information of the robot manipulator. Performances of TDC depends on the accuracy of the estimation of inertia and acceleration signal. Therefore, more accurate estimation of necessary information is aimed. In this paper, the joint models of a robot manipulator are identified by RLS algorithm, which is based on a data driven approach from random inputs. A corresponding state observer is designed based on the identified models to estimate the acceleration signals. Experimental studies of identifying the joint models are conducted to demonstrate the proposal. |
| Databáze: | OpenAIRE |
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