Kalman Filter-Based Adaptive Delay Compensation for Benchmark Problem in Real-Time Hybrid Simulation

Abstract

Real-time hybrid simulation (RTHS) is a versatile, effective, and promising experimental method used to evaluate the structural performance under dynamic loads. In RTHS, the emulated structure is divided into a numerically simulated substructure (NS) and a physically tested substructure (PS), and a transfer system is used to ensure the force equilibrium and deformation compatibility between the substructures. Owing to the inherent dynamics of the PS and transfer system (referred to as a control plant in this study), there is a time-delay between the displacement command and measurement. This causes de-synchronization between the boundary of the PS and NS, and affects the stability and accuracy of the RTHS. In this study, a Kalman filter-based adaptive delay compensation (KF-ADC) method is proposed to address this issue. In this novel method, the control plant is represented by a discrete-time model, whose coefficients are time-varying and are estimated online by the KF using the displacement commands and measurements. Based on this time-varying model, the delay compensator is constructed employing the desired displacements. The KF performance is investigated theoretically and numerically. To assess the performance of the proposed strategy, a series of virtual RTHSs are performed on the Benchmark problem in RTHS, which was based on an actual experimental system. Meanwhile, several promising delay-compensation strategies are employed for comparison. Results reveal that the proposed time-delay compensation method effectively enhances the accuracy, stability, and robustness of RTHS.

Research on overrun lag algorithm for ocean platform based on AMD control

“…Because of the complexity of the working environment, the sources of time lag of the AMD-LQG active control system are complicated, which mainly come from the following aspects: (1) the response time lag of the controlled structure; (2) the monitoring time lag of the sensors; (3) the time lag of the feedback signal transmitted from the sensors to the controller; (4) the calculation time lag of the controller; and (5) the control signal transmitted from the controller to the AMD-LQG. ( 5) the control signal caused by the transmission from the controller to the actuator; (6) the time lag generated by the actuator in [8]the process of sending the control force. In practical engineering, the design and construction of the actuator itself, as well as the signal transmission problem in the active control process, cause the time lag between the actuator and the ideal state in the actual operation process.…”

A real‐time hybrid simulation method based on multitasking loading

“…The loading time delay is the time required by the loading facilities from receiving the commands to realizing the commands. 2 For solving the loading time delay problem, a series of time delay compensation methods have been proposed, for example, the displacement prediction compensation methods based on time and measured force, [3][4][5][6][7] the compensation methods based on control theory, [8][9][10][11][12][13][14][15] and the compensation methods based on comprehensive integration concepts. [16][17][18] The calculation time delay is the time required by solving the equations of motion from receiving the measured reaction forces of the experimental substructure to generating the loading commands for the loading facilities.…”

A Novel Model-Based Adaptive Feedforward-Feedback Control Method for Real-Time Hybrid Simulation considering Additive Error Model

“…In the actual RTHS, besides the three control methods mentioned above, this study took into account the most widely used polynomial extrapolation (PE) method [37] and the recently developed Kalman flter-based adaptive delay compensation (KF-ADC) method [30]. Te swept signal used in Section 3.2 was employed as the commanded displacement to identify the nominal and inverse models and to obtain the initial parameter settings of the KF-ADC method by the least-squares method.…”

“…Second, the parameter estimation method plays a critical role in most adaptive compensation methods. A parameter estimation method with excellent ability ought to guarantee convergence, low dependency on the initial parameter setting, and high sensitivity to displacement tracking errors [30]. Tird, the robustness is difcult to guarantee, especially for the complex nonlinear testing system [31].…”