Novel feedforward controller for straight-fiber-type artificial muscle based on an experimental identification model

This paper reports on an improvement to a feedforward controller for a straight-fiber-type artificial muscle that can control the amount of contraction, stiffness, and contraction force by use of an experimental identification model. This straight-fiber-type artificial muscle has a higher contraction force and a higher contraction rate than a McKibben artificial muscle. In a previous study, we developed a feedforward controller for a straight-fiber-type artificial muscle based on a mechanical model. However, this controller could not accurately control the stiffness or the contraction force. A feedback controller was necessary to compensate for the lack of feedforward control accuracy, which increased the system complexity. In addition, the calculations of the previous controller were so complex that the microcontroller could not keep up with the sequential calculations. This is not practical when the controller is used in devices such as an assist suit. In this paper, to solve these problems, we propose a novel feedforward controller based on an experimental identification model whose calculations are simpler than the previous ones. An experimental identification model enables the feedforward controller to improve the accuracy by identifying the parameters used in the model. Also, we compare the accuracy of the proposed controller with the previous one.