Model-Based Robust Tracking Control Without Observers for Soft Bending Actuators
| Autor: | Fangfang Zhang, Guizhou Cao, Lei Yang, Gui-Bin Bian, Huo Benyan, Yanhong Liu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization Computer science Mechanical Engineering Control (management) Biomedical Engineering 02 engineering and technology Bending 021001 nanoscience & nanotechnology Tracking (particle physics) Computer Science Applications Human-Computer Interaction 020901 industrial engineering & automation Artificial Intelligence Control and Systems Engineering Control theory Feature (computer vision) Key (cryptography) Computer Vision and Pattern Recognition State (computer science) 0210 nano-technology Actuator |
| Zdroj: | IEEE Robotics and Automation Letters. 6:5175-5182 |
| ISSN: | 2377-3774 |
| Popis: | It is of great importance to improve the performance of soft bending actuators with simpler control laws. Considering that the velocity information of soft actuators cannot be measured by conventional sensors due to a contradiction between the soft body and the rigid state, this letter addresses a robust tracking controller without velocity observers to improve the tracking accuracy and simplify the control laws. First, a generalized dynamic model and related system properties are developed for the construction of controllers. Second, a novel robust tracking controller combined with an auxiliary state is utilized for soft bending actuators in the presence of system uncertainties. A key feature of the proposed controller is that it does not incorporate any information about velocities and observers. Finally, corresponding comparative simulations and experiments are performed to verify the effectiveness of the proposed controller. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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