Model-based trajectory control of robots with pneumatic actuator dynamics

Pneumatic actuators have many attributes such as natural compliance and high peak power capabilities that make them attractive for research in dynamic legged locomotion. However, the effects of nonlinear flow through the pneumatic components limit the bandwidth of actuators, thus restricting their use in a high-performance control system. We believe that a model-based control design can overcome these bandwidth limitations. In this study, we demonstrate that black-box system identification of actuator dynamics can be effectively combined with nonlinear trajectory optimization and stabilization to accomplish dynamic tasks on underactuated robots. We present two case studies: an underactuated cart-pole system with the cart driven by a pneumatic actuator and a compass gait walking robot with pneumatic toes.