Adaptive robust pressure control of variable displacement axial piston pumps with a modified reduced-order dynamic model

Variable displacement axial piston pumps (VDAPPs) are wildly used in mobile working machines and they play a key role in machine's energy-saving load sensing (LS) systems. Typically, electric load sensing (ELS) systems utilize traditional linear control methods, which only can realize limited control flexibility and performance. This study proposes and experimentally verifies an adaptive robust pressure control strategy for a VDAPP system. To facilitate the model-based controller design, a modified reduced-order dynamic modeling of VDAPPs is proposed. Furthermore, an adaptive robust backstepping control strategy is designed to deal with the dynamic nonlinearities and parametric uncertainties of the VDAPP system for achieving accurate pressure tracking. The controller design consists of two steps, processing the pump pressure tracking and the axial angle control, respectively. Comparative experiments and simulations with different working conditions were performed to validate the advantages of the proposed control strategy. The proposed controller achieved higher pressure tracking accuracy and it showed great capability in dealing with dynamic nonlinearities, uncertainties, and time-varying disturbances.

Automated summary

This study proposes an adaptive robust pressure control strategy for variable displacement axial piston pumps (VDAPPs), which deals with dynamic nonlinearities and parametric uncertainties to achieve accurate pressure tracking. The proposed controller shows higher pressure tracking accuracy and great capability in handling dynamic nonlinearities, uncertainties, and time-varying disturbances.