High-precision trajectory tracking of hydraulic passive load-sensitive systems via disturbance observer-based adaptive robust control

Passive Load-Sensitive Systems (PLSS) deliver outstanding energy efficiency in fluid power actuation, yet their use in high-precision servo applications remains restricted by strong model nonlinearities, parametric uncertainties, and external load disturbances. This work establishes a refined nonlinear dynamic model that explicitly captures the time-varying displacement behavior and multi-physics coupling effects inherent to PLSS. On the basis of the derived model, a Disturbance Observer-augmented Adaptive Robust Control (DO-ARC) framework is developed. The proposed method integrates model-based feedforward compensation to handle dominant parametric mismatches, while a specially constructed disturbance observer provides real-time estimation and active attenuation of matched and mismatched lumped disturbances. By functionally separating disturbance observation from adaptive parameter estimation, the controller achieves guaranteed transient performance and uniformly bounded tracking errors, while reducing the reliance on high-gain robust feedback terms. Experimental validation shows that the proposed DO-ARC enhances trajectory tracking accuracy by 27% relative to conventional adaptive robust control under nominal conditions, and yields an 18.0% improvement in tracking accuracy under persistent external load disturbances, while retaining the excellent energy-saving performance inherent to the PLSS structure. This work provides a viable control solution for deploying energy-efficient passive load-sensitive systems in high-performance servo applications. © 2026 Elsevier Ltd.