This paper presents an adaptive backstepping controller for a mechanism of pneumatic muscle actuators via an adaptive extended state observer. A dynamic model of the mechanism is established with two unknown parameters estimated by using adaptive laws. An adaptive extended state observer is established to estimate total disturbances and states of the mechanism. Moreover, adaptive extended state observer gains are obtained by adaptive laws and parallel D-eigenvalues, whose time-varying multiplier nth-order derivatives are derived by tracking differentiators. Finally, a nonlinear adaptive backstepping controller is designed and the effectiveness of the proposed method is expressed by experimental results.

This paper presents a Tornambe controller (TC) for a two-degree-of-freedom (DOF) parallel mechanism of pneumatic muscle actuators (PMAs) based on tracking differentiators (TDs). A dynamic nonlinear system is established for the 2-DOF parallel mechanism of PMAs. TC is designed for improving control performance of the dynamic nonlinear system. The TDs are utilized to obtain high order derivatives of tracking errors, which are required by TC. Moreover, stability analysis of the dynamic nonlinear system is shown by a Lyapunov approach. Finally, experimental results are shown to verify the effectiveness of the proposed control method in this paper.

This paper presents a nonlinear error feedback controller for a pneumatic soft bionic fin based on an extended state observer. Manufacturing process is shown for a bionic stingray with the pneumatic soft bionic fin. A test experiment is carried out for a driving part in the pneumatic soft bionic fin by upper chamber inflated and lower chamber inflated with different internal pressures. A dynamic nonlinear system is established for the pneumatic soft bionic fin by test experiment results and kinematic modeling. Total disturbances of the dynamic nonlinear system are estimated and compensated by the extended state observer and the nonlinear error feedback controller, respectively. Moreover, both the convergence of the extended state observer and stability of the dynamic nonlinear system are proved by Lyapunov approach. Finally, simulation results are shown to verify the effectiveness of the proposed control method for the pneumatic soft bionic fin.