A GA-Based Parameters Tuning Method for Active Disturbance Rejection Control of Hydraulic Spherical Motion Actuator

This paper presents a parameters tuning method based on the genetic algorithm for an active disturbance rejection controller (ADRC) of a hydraulic spherical motion actuator. The dynamic model of the hydraulic spherical motion actuator derived by Lagrange approach is evidently a nonlinear coupling system with parameters time-varying and model uncertainties, which will inevitably influence the tracking performance. To improve the trajectory tracking performance, a robust ADRC based on genetic optimization, which consists of a nonlinear tracking differentiator, extended state observer, and nonlinear state error feedback, is proposed. Utilize the genetic algorithm to optimize the parameters of the ADRC automatically. In the process of ADRC parameter optimization, the evaluation function is established, in which the dynamic performance and the input constraints of the controller are comprehensively considered. Finally, the effectiveness of the proposed approach is validated via the simulation results.