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Adaptive robust control of soft bending actuators: an empirical nonlinear model-based approach

Cong Chen, Jun Zou

2021Journal of Zhejiang University. Science A16 citationsDOI

Abstract

Soft robotics, compared with their rigid counterparts, are able to adapt to uncharted environments, are superior in safe human-robot interactions, and have low cost, owing to the native compliance of the soft materials. However, customized complex structures, as well as the nonlinear and viscoelastic soft materials, pose a great challenge to accurate modeling and control of soft robotics, and impose restrictions on further applications. In this study, a unified modeling strategy is proposed to establish a complete dynamic model of the most widely used pneumatic soft bending actuator. First, a novel empirical nonlinear model with parametric and nonlinear uncertainties is identified to describe the nonlinear behaviors of pneumatic soft bending actuators. Second, an inner pressure dynamic model of a pneumatic soft bending actuator is established by introducing a modified valve flow rate model of the unbalanced pneumatic proportional valves. Third, an adaptive robust controller is designed using a backstepping method to handle and update the nonlinear and uncertain system. Finally, the experimental results of comparative trajectory tracking control indicate the validity of the proposed modeling and control method.

Topics & Concepts

Control theory (sociology)Soft roboticsActuatorNonlinear systemController (irrigation)Parametric statisticsBacksteppingControl engineeringPneumatic actuatorRobotRoboticsBendingComputer scienceEngineeringAdaptive controlArtificial intelligenceControl (management)Structural engineeringMathematicsAgronomyQuantum mechanicsStatisticsPhysicsBiologySoft Robotics and ApplicationsElevator Systems and ControlMechanical Circulatory Support Devices
Adaptive robust control of soft bending actuators: an empirical nonlinear model-based approach | Litcius