Cascaded Model Predictive Control of Underactuated Bipedal Walking with Impact and Friction Considerations

Date

2023-12-19

Author

Sovukluk, Sait
Ott, Christian
Ankaralı, Mustafa Mert

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This study demonstrates a cascaded model predictive control (C-MPC) method for input constrained control of underactuated planar bipedal walking with any predefined sta-bilizable trajectory. Our approach aims to increase the trajectory tracking performance of the system and produce realistic and applicable responses while respecting friction constraints and considering impact dynamics. Primarily focusing on zero dynamics with PD (ZD+PD) control, this proposed control method constitutes a second layer controller on top of the well-known trajectory tracking controllers for underactuated bipedal walking systems. We successfully implement this model-based controller and test against large modeling errors, noises, and disturbances, where the conventional ZD+PD control fails to maintain stability.

URI

https://hdl.handle.net/11511/108149

DOI

https://doi.org/10.1109/humanoids57100.2023.10375153

Conference Name

2023 IEEE-RAS International Conference on Humanoid Robots

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Citation Formats

S. Sovukluk, C. Ott, and M. M. Ankaralı, “Cascaded Model Predictive Control of Underactuated Bipedal Walking with Impact and Friction Considerations,” presented at the 2023 IEEE-RAS International Conference on Humanoid Robots, Austin, Amerika Birleşik Devletleri, 2023, Accessed: 00, 2024. [Online]. Available: https://hdl.handle.net/11511/108149.