Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control

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...

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Bibliographic Details
Published in:IEEE access 2015, Vol.3, p.235-248
Main Authors: Zhakatayev, Altay, Rubagotti, Matteo, Varol, Huseyin Atakan
Format: Article
Language:English
Subjects:
Actuation
Algorithms
Closed loop systems
Design methodology
Embedded Optimization
Heuristic algorithms
Human engineering
Human-robot interaction
Kinematics
Model Predictive Control
Nonlinear control
Nonlinear systems
Nonlinearity
Optimal control
Optimization
Optimization Algorithms
Predictive control
Robot control
Robot Manipulation
Robotics
Robots
State variable
Stiffness
Throwing
Trajectory control
Variable Stiffness Actuation
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Summary: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 dynamicsdynamics 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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2015.2418157