Parameter Identification and Model-Based Nonlinear Robust Control of Fluidic Soft Bending Actuators

Soft actuators are of great interests in recent years due to inherent compliance and adaptability. However, most of current studies focus on the physical actuation phenomenon and their fabrication, few results can be found on the modeling and closed-loop control due to their complicated elastic deformation. This paper studies physical modeling, parameter identification, and model-based nonlinear robust control for fluidic soft bending actuators governed by high-speed
on–off
solenoid valves. With the dynamic complexity and characteristics of fluidic soft actuators, the system has been described by two parts: motion dynamics and air dynamics. A second-order transfer function is used for the motion dynamics which describes the behavior from driving pneumatic pressure to soft actuator bending angle, and the model parameters are identified by with different operating frequencies. The nonlinear physical modeling of air dynamics which describes the behavior from control voltage to driving pneumatic pressure is also built and its parameters are identified by using the least square method. Based on the identified high-order model, a nonlinear robust control algorithm is developed for soft actuator by backstepping design to deal with nonlinearities and uncertainties. Experimental results show that the closed-loop stability is guaranteed and the good tracking performance is achieved by the proposed method.