Abstract Summary
Real-time Hybrid Simulation (RTHS) is an effective method for estimating the dynamic response of structural systems. The system splits into a numerical substructure (NS) and an experimental substructure (ES). The NS is solved numerically, while a servo-hydraulic actuator imposes boundary conditions (typically displacements) over the ES. The command signal is based on the current NS response. This framework scheme has been demonstrated to work very well in different research applications. However, it is limited when the displacement is imposed on the high stiffness ES (e.g., axial DOF of a column). A possible solution is to impose forces over the ES instead of displacements. However, the literature shows that the load cells add considerable noise to the measured signal, causing high tracking errors and could cause instability in the simulation. To sort out this problem, the literature proposes adding a compliance spring between the piston of the actuator and the ES. The compliance properties are known a priori and considered deterministic, adding flexibility to the system. With this scheme, it is possible to command forces to the actuator and control them by measuring the spring elongation and the restoring force from a load cell. However, developing dynamic compensation for force-based RTHS is challenging due to the uncertainty of specimen-compliance-actuator interaction. Therefore, this study proposes a force-based RTHS with robust compliance compensation. The compliance spring and the load cell will have uncertainties in their properties. Robust adaptive model-based compensation will be employed to overcome force-tracking errors between substructures. The proposed methodology will be verified in a virtual RTHS environment, where parametric studies will be considered to check the system's robustness over uncertain compliance. In addition, specimens with high stiffness will be tested to evaluate and verify the proposed scheme, which will be implemented on a force-based RTHS considering the axial DOF of the specimen.
