A fingerprint method for variability and robustness analysis of stochastically controlled cellular actuator arrays

Abstract

In this paper we present a 'fingerprint method' for modeling and subsequently characterizing stochastically controlled actuator arrays. The actuator arrays are built from small actuator cells with structural elasticity. These cells are controlled using a bistable stochastic process wherein all cells are given a common input probability (control) value which they use to determine whether to actuate or relax. Arranging the cells in different networks gives different actuator array properties, which must be found before the actuator arrays can be applied to manipulators. The fingerprint method is used to describe and automatically generate every possible stochastic actuator array topology for a given number of cells, and to calculate actuator array properties such as: travel, required actuator strength/displacement, force range, force variance, and robustness for any array topology. The properties of several illustrative examples are shown and a discussion covers the importance of the properties, and trends between actuator array layouts and their properties. Finally, results from a validation experiment using a stochastically controlled solenoid array are presented.

Dynamic cellular actuator arrays and the expanded fingerprint method for dynamic modeling

“…The cells were operated using a bi-stable stochastic all-on all-off broadcast control method to reduce wiring complexity, control signals, and hysteresis error [9]. [10] expanded upon the results of [8] looking more specifically into force descritization and presented methods for generating all possible cell array topologies given a limited number of cells. This later result is critical to designers wanting to explore the possibilities of the cell arrays and select a topology specific to their criteria.…”

“…In [11], an expanded version of the fingerprint method presented in [10] allows for the dynamic analysis cell array actuators built from cells based on Miga NanoMuscle 704 SMA actuators connected in series with coil springs. The cell model for these actuator arrays was a modified Hill-Type model shown in Fig.…”

“…Having more cells in series tends to give an array more displacement, more in parallel gives more force and higher robustness, and having a non-uniform structure can give higher force discretization and more fine-tuned control [10]. A physical cell has two significant mass elements connected by the SMA actuator and spring.…”

“…All cells connect directly to masses and no mass is connected directly to any other mass. Furthermore, the design restrictions in [10] are upheld, namely that an array consists of discrete equal relaxed length layers and all cells are identical. This last restriction will be relaxed in future work but is maintained here to simplify explination of the theory.…”

“…This last restriction will be relaxed in future work but is maintained here to simplify explination of the theory. The array topology can be represented using the fingerprint method from [10], a layer based set of three row matrices encoding the connection information of the array. The fingerprint transcription consists of segmenting the array into layers just after the cells and before the incoming connecting structures.…”