Abstract
Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human-robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently the focus is shifting to the control of these systems. Control of VSA robots is challenging due to the intrinsic nonlinearity of their dynamics and the need to satisfy constraints on input and state variables. Contrary to the partially open-loop state-of-the-art approaches, in this paper, we present a close-loop control framework for VSA robots leveraging recent increases in computational resources and advances in optimization algorithms. In particular, we generate reference trajectories by means of open-loop optimal control, and track these trajectories via nonlinear model predictive control in a closed-loop manner. In order to show the advantages of our proposed scheme with respect to the previous (partially open-loop) ones, extensive simulation and real-world experiments were conducted using a two link planar manipulator for a ball throwing task. The results of these experiments indicate that the closed-loop scheme outperforms the partially open loop one due to its ability to compensate for model uncertainties and external disturbances, while satisfying the imposed constraints.
| Original language | English |
|---|---|
| Article number | 7073614 |
| Pages (from-to) | 235-248 |
| Number of pages | 14 |
| Journal | IEEE Access |
| Volume | 3 |
| DOIs | |
| Publication status | Published - 2015 |
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Keywords
- Embedded Optimization
- Model Predictive Control
- Optimization Algorithms
- Robot Manipulation
- Variable Stiffness Actuation
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
- Materials Science(all)
Cite this
Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control. / Zhakatayev, Altay; Rubagotti, Matteo; Varol, Huseyin Atakan.
In: IEEE Access, Vol. 3, 7073614, 2015, p. 235-248.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control
AU - Zhakatayev, Altay
AU - Rubagotti, Matteo
AU - Varol, Huseyin Atakan
PY - 2015
Y1 - 2015
N2 - Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human-robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently the focus is shifting to the control of these systems. Control of VSA robots is challenging due to the intrinsic nonlinearity of their dynamics and the need to satisfy constraints on input and state variables. Contrary to the partially open-loop state-of-the-art approaches, in this paper, we present a close-loop control framework for VSA robots leveraging recent increases in computational resources and advances in optimization algorithms. In particular, we generate reference trajectories by means of open-loop optimal control, and track these trajectories via nonlinear model predictive control in a closed-loop manner. In order to show the advantages of our proposed scheme with respect to the previous (partially open-loop) ones, extensive simulation and real-world experiments were conducted using a two link planar manipulator for a ball throwing task. The results of these experiments indicate that the closed-loop scheme outperforms the partially open loop one due to its ability to compensate for model uncertainties and external disturbances, while satisfying the imposed constraints.
AB - Variable stiffness actuation has recently attracted great interest in robotics, especially in areas involving a high degree of human-robot interaction. After investigating various design approaches for variable stiffness actuated (VSA) robots, currently the focus is shifting to the control of these systems. Control of VSA robots is challenging due to the intrinsic nonlinearity of their dynamics and the need to satisfy constraints on input and state variables. Contrary to the partially open-loop state-of-the-art approaches, in this paper, we present a close-loop control framework for VSA robots leveraging recent increases in computational resources and advances in optimization algorithms. In particular, we generate reference trajectories by means of open-loop optimal control, and track these trajectories via nonlinear model predictive control in a closed-loop manner. In order to show the advantages of our proposed scheme with respect to the previous (partially open-loop) ones, extensive simulation and real-world experiments were conducted using a two link planar manipulator for a ball throwing task. The results of these experiments indicate that the closed-loop scheme outperforms the partially open loop one due to its ability to compensate for model uncertainties and external disturbances, while satisfying the imposed constraints.
KW - Embedded Optimization
KW - Model Predictive Control
KW - Optimization Algorithms
KW - Robot Manipulation
KW - Variable Stiffness Actuation
UR - http://www.scopus.com/inward/record.url?scp=84959852046&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959852046&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2015.2418157
DO - 10.1109/ACCESS.2015.2418157
M3 - Article
VL - 3
SP - 235
EP - 248
JO - IEEE Access
JF - IEEE Access
SN - 2169-3536
M1 - 7073614
ER -