Simultaneous position-stiffness control of antagonistically driven twisted-coiled polymer actuators using model predictive control

Super-coiled polymer (SCP) artificial muscles have many interesting properties that show potentials for making high performance bionic devices. To realize human-like robotic devices from this type of actuator, it is important for the SCP driven mechanisms to achieve human-like performance, such as compliant behaviors through antagonistic mechanisms. This paper presents the simultaneous position-stiffness control of an antagonistic joint driven by hybrid twisted-coiled polymer actuation bundles made from Spandex and nylon fibers, which is a common human compliant behavior. Based on a linear model of the system, which is identified and verified experimentally, a controller based on model predictive control (MPC) is designed. The MPC performance is enhanced by the incorporation of time delay estimation to estimate model variations and external disturbances. The controlled system is verified through simulations and experiments. The results show the controller's ability to control the joint angle with the highest position error of 0.6 degrees while changing joint stiffness, verified with step command and sinusoidal reference with composite frequencies of 0.01Hz to 0.1Hz.