Power assist system with motion estimation using constrained predictive functional control

Recently, many types of control methods using electromyogram signals have been proposed for power-assist robots or electric prosthesis. However, they do not easily adapt to unknown environment or conditions. Therefore, we propose a new power-assist system using model predictive control (MPC) that can realize a stable power-assist and predict the future human fingers touque and the future trajectory in real time. Our power-assist system is composed of a combination of an MPC system based on an expansion plant model and a predictive functional control system based on a plant model.