Novel Two-Stage Adaptive Delay Compensation Method Based on a System Nominal Model for Real-Time Hybrid Simulation

In real-time hybrid simulation (RTHS), delay compensation is one of the crucial issues that affect the accuracy and reliability of test data. A novel two-stage adaptive delay compensation method is presented in this study to enhance compensation accuracy and robustness. This method employs a Kalman filter-based adaptive nominal model compensation (KF-ANMC) in the first stage to enhance the compensation robustness against system uncertainties. Inverse control compensation serves as the second stage compensation to eliminate the system delay and to improve the accuracy of RTHS. Through computational simulations and real tests of RTHS for high-speed trains, the effectiveness and robustness of the proposed method are validated, and the influence of relevant parameters on its performance is thoroughly analyzed. Results indicate that the proposed method exhibits great robustness against system uncertainties and superior delay compensation performance. Moreover, this study shows that the proposed method is endowed with reduced dependence on the orders of KF-ANMC and nominal system model, and parameter initialization.