Hysteresis inversion-free predictive compensation control for soft pneumatic actuators based on a global Koopman modeling strategy

Abstract

Soft pneumatic actuators (SPAs) have increasing applications in soft robotic design owing to their good compliance, excellent adaptability, and high force density characteristics. However, the inherent hysteresis nonlinearity severely degrades the control performance of SPAs. To compensate for the hysteresis effect, one solution is to build an inverse mathematical model. Nevertheless, in this method, the control performance still highly depends on the accuracy of the built inverse model. At the same time, the computational burden of deriving the inverse model is overwhelming. In addition, the physical constraints of the input pressure of SPAs are hardly handled by the inversion-based method. This paper proposes an inversion-free model predictive controller (IFMPC), which is designed based on a global Koopman linear model (GKLM). In the above GKLM-IFMPC strategy, the inverse hysteresis model is not required. Instead, a global hysteresis model can be established without considering the effect of rate-dependent property. Additionally, the control law is derived in an explicit form. With the constrained quadratic programming technique, the proposed method still works well when dealing with the physical constraints of SPAs. To verify the effectiveness of the proposed method, several comparative experiments are performed on a two-dimensional (2D) SPA. The results show that the proposed hysteresis global modeling and control framework has satisfactory tracking performance over some existing strategies even with strong hysteresis nonlinearity.