This paper presents the road simulator control technology for reproducing a road input signal to implement real road data. The simulator consists of a hydraulic pump, a servo valve, a hydraulic actuator and its control equipment. QFT (Quantitative Control Theory) is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with a low order transfer function G(s) and a pre-filter F(s) for a parametric uncertainty model. A force controller is designed to communicate the control signal between the simulator and digital controller. Tracking specification is satisfied with upper and lower bound tolerances on the steep response of the system to the reference signal. The efficacy of the QFT force controller is verified through the numerical simulation in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under an uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller on a real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.

This paper presents the design of a quantitative feedback control system for a three-axis hydraulic road simulator. The road simulator is a multiple input-output (MIMO) system with parameter uncertainties which should be compensated with a robust control method. The objective of the present paper is to reproduce the random input signal or real road vibration signal by three hydraulic cylinders. The replaced m 2 MISO equivalent control system is suggested, which satisfies the design specification of the original mxm MIMO control system by decoupling each of the three axes. Quantitative Feedback Theory (QFT) is used to control the simulator. The QFT illustrates a tracking performance of the closed-loop controller with low order transfer function G (s) and pre-filter F (s) having the minimum bandwidth for the uncertain plant with parameter uncertainty. The efficacy of the designed controller is verified through dynamic simulation, which is co-simulated with hydraulic models of Matlab and Adams multi-body. The simulation and the experimental results show that the proposed control technique works well for uncertain hydraulic plant systems.