Control of Scalable Wet SMA Actuator Arrays

Leslie Flemming, Minnesota State University Mankato
Stephen Mascaro, University of Utah


This paper presents a new control method to drive an array of wet Shape Memory Alloy actuators utilizing a Matrix Manifold and Valve system (MMV). The MMV architecture allows a vast DOF robotic system to be controlled using limited number of resources. Using biological inspiration, the robotic system contains a network of “blood vessels” transporting fluid to the various “muscle” actuators. In general, an array of N2wet actuators can be controlled by 2N+2 fluidic valves, resulting in a scalable architecture. This would allow robots to contain a vast number of actuators like the human body, and be controlled in a scalable manner. The initial prototype contains a 4x4 array of 16 actuators controlled by 10 solenoid valves, where 25% of the actuators can be activated at any one time. Since only a subset of the actuators can be activated at any time, various methods of scheduling the resources (i.e. valves) are investigated, as well as various ways to define the error or difference between the desired and actual states of the array. The fluidic impedance of the system is taken into account in order to optimize the control. Results of simulation show that new scheduler options and definitions of error improve the performance of the system by a factor of 10 when operating the array near its maximum capacity.