System identification and robust position control for electro-hydraulic servo system using hybrid model predictive control

Abstract

This paper examined system identification using grey-box model estimation and position-tracking control for an electro-hydraulic servo system (EHSS) using hybrid controller composed of proportional-integral control (PIC) and model predictive control (MPC). The nonlinear EHSS model is represented by differential equations. We identify model parameters and verify their accuracy against experimental data in MATLAB to evaluate the validity of this mathematical model. To guarantee improved performance of EHSS and precision of cylinder position, we propose a hybrid controller composed of PIC and MPC. The controller is designed using the Control Design and Simulation module in the Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW). A LabVIEW-based experimental rig is developed to apply the proposed controller in real time. Then, the validity and performance superiority of the hybrid controller were confirmed by comparing them with the MPC and PIC results. Results of real-life experiments show improved robustness and dynamic and static properties of EHSS.