Paper Info
Title
Bioinspired adaptive control for artificial muscles
Abstract
The new field of soft robotics offers the prospect of replacing existing hard actuator technologies by artificial muscles more suited to human-centred robotics. It is natural to apply biomimetic control strategies to the control of these actuators. In this paper a cerebellar-inspired controller is successfully applied to the real-time control of a dielectric electroactive actuator. To analyse the performance of the algorithm in detail we identified a time-varying plant model which accurately described actuator properties over the length of the experiment. Using synthetic data generated by this model we compared the performance of the cerebellar-inspired controller with that of a conventional adaptive control scheme (filtered-x LMS). Both the cerebellar and conventional algorithms were able to control displacement for short periods, however the cerebellar-inspired algorithm significantly outperformed the conventional algorithm over longer duration runs where actuator characteristics changed significantly. This work confirms the promise of biomimetic control strategies for soft-robotics applications.
Year
DOI
Venue
2013
10.1007/978-3-642-39802-5_27
Living Machines
Keywords
Field
DocType
conventional adaptive control scheme,actuator property,conventional algorithm,biomimetic control strategy,cerebellar-inspired controller,artificial muscle,dielectric electroactive actuator,actuator characteristic,cerebellar-inspired algorithm,bioinspired adaptive control,existing hard actuator technology,real-time control
Control theory,Simulation,Computer science,Soft robotics,Electroactive polymers,Control engineering,Synthetic data,Artificial intelligence,Adaptive control,Artificial muscle,Robotics,Actuator
Conference
Citations 
PageRank 
References 
6
1.14
7
Authors
6
Name
Order
Citations
PageRank
Emma D. Wilson1102.68
Tareq Assaf2164.55
Martin J. Pearson321526.34
Jonathan Rossiter45619.66
Sean R. Anderson58914.87
John Porrill635285.11