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Enhanced Dynamic Model of Pneumatic Muscle Actuator with Elman Neural Network
Joint Authors
Piteľ, Ján
Židek, Kamil
Hošovský, Alexander
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-02
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
To make effective use of model-based control system design techniques, one needs a good model which captures system’s dynamic properties in the range of interest.
Here an analytical model of pneumatic muscle actuator with two pneumatic artificial muscles driving a rotational joint is developed.
Use of analytical model makes it possible to retain the physical interpretation of the model and the model is validated using open-loop responses.
Since it was considered important to design a robust controller based on this model, the effect of changed moment of inertia (as a representation of uncertain parameter) was taken into account and compared with nominal case.
To improve the accuracy of the model, these effects are treated as a disturbance modeled using the recurrent (Elman) neural network.
Recurrent neural network was preferred over feedforward type due to its better long-term prediction capabilities well suited for simulation use of the model.
The results confirm that this method improves the model performance (tested for five of the measured variables: joint angle, muscle pressures, and muscle forces) while retaining its physical interpretation.
American Psychological Association (APA)
Hošovský, Alexander& Piteľ, Ján& Židek, Kamil. 2015. Enhanced Dynamic Model of Pneumatic Muscle Actuator with Elman Neural Network. Abstract and Applied Analysis،Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1052135
Modern Language Association (MLA)
Hošovský, Alexander…[et al.]. Enhanced Dynamic Model of Pneumatic Muscle Actuator with Elman Neural Network. Abstract and Applied Analysis No. 2015 (2015), pp.1-16.
https://search.emarefa.net/detail/BIM-1052135
American Medical Association (AMA)
Hošovský, Alexander& Piteľ, Ján& Židek, Kamil. Enhanced Dynamic Model of Pneumatic Muscle Actuator with Elman Neural Network. Abstract and Applied Analysis. 2015. Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1052135
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1052135