Abstract
Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training.
Highlights
Making robots ‘soft’ significantly increases the range of environments in which they can operate, allowing them, for example, to interact safely with people
The linear control scheme gives steady-state RMS errors of 0.011 mm when the Dielectric elastomer actuators (DEAs) is excited over a reduced range, such that the dynamics can be approximated as linear [7])
A simpler learning rule that does not include the effect of previous gains was tested on the simulated system and gave very similar performance to that shown in figure 8. These results show that a bioinspired control scheme, based on cerebellar calibration of the vestibulo-ocular reflex (VOR), is capable of compensating for the plant nonlinearities of a DEA-based actuator
Summary
Making robots ‘soft’ significantly increases the range of environments in which they can operate, allowing them, for example, to interact safely with people (for recent review, see [1]). Robots made wholly or in part from materials that change the shape when subjected to force are more difficult to control than rigid robots [2]. This is true for compliant actuators, capable of muscle-like high strain, which have been manufactured from a wide variety of materials including electroactive polymers (EAPs) [3] that can undergo large deformations in response to electrical stimuli. Dielectric elastomer actuators (DEAs) are an example of compliant EAP-based actuators with high energy density, large strain capability and a relatively fast response [4] As such, they possess many of the desirable properties of biological muscle [5] and have attracted significant interest in the field of soft robotics research. Even with recent advances in materials science and manufacturing processes, the precise control of DEAs remains a non-trivial problem owing to a number of intrinsic nonlinear and time variant characteristics as illustrated schematically in figure 1
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