Identification of a vertical hopping robot model via harmonic transfer functions

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2016-05-01

Author

Uyanik, Ismail
Ankaralı, Mustafa Mert
Cowan, Noah J.
Saranlı, Uluç
Morgul, Omer

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A common approach to understanding and controlling robotic legged locomotion is the construction and analysis of simplified mathematical models that capture essential features of locomotor behaviours. However, the representational power of such simple mathematical models is inevitably limited due to the non-linear and complex nature of biological locomotor systems. Attempting to identify and explicitly incorporate key non-linearities into the model is challenging, increases complexity, and decreases the analytic utility of the resulting models. In this paper, we adopt a data-driven approach, with the goal of furnishing an input-output representation of a locomotor system. Our method is based on approximating the hybrid dynamics of a legged locomotion model around its limit cycle as a Linear Time Periodic (LTP) system. Perturbing inputs to the locomotor system with small chirp signals yield the input-output data necessary for the application of LTP system identification techniques, allowing us to estimate harmonic transfer functions (HTFs) associated with the local LTP approximation to the system dynamics around the limit cycle. We compare actual system responses with responses predicted by the HTF, providing evidence that data-driven system identification methods can be used to construct models for locomotor behaviours.

Subject Keywords

System identification, Harmonic transfer functions, Legged locomotion, Periodic systems

URI

https://hdl.handle.net/11511/47943

Journal

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

DOI

https://doi.org/10.1177/0142331215583327

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

I. Uyanik, M. M. Ankaralı, N. J. Cowan, U. Saranlı, and O. Morgul, “Identification of a vertical hopping robot model via harmonic transfer functions,” TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, pp. 501–511, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47943.