Designing an Axial Piston Pump Displacement Controller for Varying Reference Trajectory Based on Model Predictive Control
Year: 2025
Type: article
Abstract: Variable displacement hydraulic pumps are applied to a wide range of fields for energy saving, but the displacement control is easily influenced by changes in dynamic characteristics depending on the operating point, and the control valve and pump displacement have constraints. Therefore, high control performance cannot be obtained without considering these nonlinearities. In a previous study, we designed a pump displacement control system based on a model predictive control (MPC) method that can consider various constraints at the design step. However, the previously presented control system requires the pre-designed reference trajectory of the pump displacement at the design step. Furthermore, the pump displacement cannot track to other reference trajectories. In this study, an extended MPC proposed in a previous study is combined with an adaptive model matching-based MPC with an inverse optimization method, proposed as a control system by the authors. This compensates for modeling errors and optimizes the weights of the evaluation function to achieve tracking to arbitrary time-varying reference trajectories using a virtual reference signal. To improve tracking performance, variable control input constraints, which are also proposed in our previous study, are introduced. The tracking performance of this control system for arbitrary time-varying reference trajectories have been verified by experiments. The experimental results have shown that the proposed control system achieves high tracking accuracy for an arbitrary time-varying reference trajectory and significantly reduces the man-hours for the parameter design of the control system.
Authors: Tsuyoshi Yamada, Editorial Office, Kazuhisa Ito
Institution: Shibaura Institute of Technology
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415878024