Adaptive Hydraulic System Control Using the Weighted Recursive Least Squares (WRLS) Method

Determining the optimal controller settings in adaptive control systems for hydraulic drives is challenging. This is due to nonlinearities, parameter variability, and the influence of external disturbances. The proposed method assumes that varying operating conditions and control errors result in dynamic changes in system parameters. The controller parameters were adjustedvia the indirect identification of a linear model combined with the weighted recursive least squares (WRLS) method, ensuring continuous model adaptation to current operating conditions.The identification process included signal filtering using differentiating filters, which enabled precise derivative estimation in the presence of measurement noise, which is a key aspect of adaptive control. The applied filters allowed us to accurately determine system dynamics and improve parameter estimation accuracy. The experimental results confirmed that the application of adaptive control using the WRLS algorithm significantly enhances hydraulic system precision. In particular, in the system under study, the use of the WRLS method, with the additional adjustment of PD controller settings based on the control error, led to a satisfactory improvement in tracking error.