Robust passive tracking control for an uncertain soft actuator using robust right coprime factorization

As a research of human arm activities, the research of soft actuator is one of the important topics in the field of robotics. This article is concerned with the robust passive tracking control for an uncertain soft actuator by robust right coprime factorization (RRCF). First, applying the recursive least squares identification algorithm, the identification of the actuator modeling is studied by which the parameter of radius is estimated by using the experimental data. Second, the passivity of the soft actuator with inflatable rubber tube is discussed; meanwhile, the robustness of the soft actuator is ensured by the designed robust controllers. Third, by combining the RRCF and integral sliding mode control methods, the tracking performance is improved, for the soft actuator with time-varying radius. Finally, the proposed methods are confirmed by the simulation with experimental data.

Automated summary

This article focuses on robust passive tracking control of uncertain soft actuators using the robust right coprime factorization (RRCF) method. Parameter estimation, controller design, and simulation verification were conducted based on experimental data to improve the tracking performance of soft actuators.