Dynamic Surface-Based Adaptive Active Disturbance Rejection Control of Electrohydrostatic Actuators

The control accuracy and stability of the electrohydrostatic actuator (EHA) are directly impacted by parameter uncertainty, disturbance uncertainty, and non-matching disturbance, which negatively impacts aircraft rudder maneuvering performance and even results in rudder chatter. A dynamic surface-based adaptive active disturbance rejection control (DSAADRC) is proposed as a solution for these issues. It does this by developing a novel parametric adaptive law driven by the combination of tracking error, parameter estimation error, and state estimation error to estimate the unknown parameters, using three low-order ESOs to estimate and compensate the uncertain disturbances online, and employing a dynamic surface method to obtain the differential values of virtual control signals in the backstepping method to deal with non-matching disturbances. In this research, a Lyapunov stability analysis demonstrates that the method can achieve the position tracking accuracy of the EHA under time-varying external disturbances after first establishing an EHA dynamics model with nonlinearity and uncertainty, followed by the design of an adaptive active disturbance rejection control method based on dynamic surfaces for the uncertainties and perturbations. In contrast to control strategies like Robust Control (RC) and Adaptive Robust Control (ARC), simulation and experiment comparison shows that the method has stronger anti-disturbance under time-varying external disturbances.

Automated summary

This research proposes a dynamic surface-based adaptive active disturbance rejection control (DSAADRC) method for the electrohydrostatic actuator (EHA). The method estimates unknown parameters, compensates for uncertain disturbances, and handles non-matching disturbances using a combination of adaptive law, disturbance estimation, and dynamic surface method. The Lyapunov stability analysis demonstrates that the method achieves position tracking accuracy under time-varying external disturbances, and simulation and experiment comparison shows its stronger anti-disturbance capability compared to other control strategies.