ABSTRACT
The soft manipulator actuated parallel with contractile and extensor pneumatic artificial muscles (PAMs) can perform continuous operations and vary stiffness. Due to the hysteresis nonlinearity of PAMs and parallel driving, the manipulator shows coupled hysteresis with stiffness-dependent and rate-dependent characteristics, causing inaccurate positioning performance. This paper firstly proposes a comprehensive dynamic model consisting of two parts in series to predict the manipulator dynamical behaviors with coupled hysteresis. Furthermore, a decoupled inverse compensation and decoupling control on the basis of the proposed model is conducted on the soft manipulator. Experimental results and comparisons illustrate the high precision and strong generalization ability of the proposed model and the validity of the compensator in mitigating the coupled dynamic hysteresis of the system.
ABSTRACT
This paper focuses on the data-driven adaptive control problem of the shape memory alloy (SMA) actuators subject to uncertainties, input saturation and prescribed performance. Firstly, the uncertainties estimation method, anti-windup technology, and prescribed performance function are introduced to deal with uncertain nonlinearity, input constraint, and prespecified performance, respectively. Meanwhile, a general approach about designing asymmetrical convergence bound is presented to increase the flexibility of creating convergence area. Secondly, taking uncertainties, input saturation, and asymmetrical convergence bound into consideration, we design an integral terminal sliding mode controller to guarantee the prescribed tracking accuracy without using the knowledge of the SMA actuators model. Further, the stability of the controller and the boundedness of the convergence error are proved by rigorous theoretical analysis. Finally, the success and superiority of our controller are verified by the SMA actuator experiments.
