Real-time hybrid simulation (RTHS) is an interesting method for studying the performance of structures subjected to dynamic loading. RTHS decomposes a structure into partitioned physical and numerical sub-structures that are coupled together through actuation systems. The sub-structuring approach is particularly attractive for studying large-scale problems since it allows for setting up large-scale structures with thousands of degrees of freedom in numerical simulations while specific components can be studied experimentally. Due to the RTHS system dynamics, there is an inevitable time delay that affects accuracy and stability of the simulation. Several tracking control algorithms have been proposed to compensate time delay and improve the accuracy, however, robustness still presents challenges to obtain successful simulation results. In this paper, a Conditional Adaptive Time Series (CATS) compensator is proposed based on the principles of the Adaptive Time Series compensator (ATS) for a benchmark problem that consists of a three-story shear frame with one degree of freedom (DOF) in a virtual RTHS (vRTHS) that considers numerical and experimental models subjected to earthquake loading. A recursive least square (RLS) algorithm is adopted for the parameter estimation of the controller to reduce computational efforts in the simulation. The performance and robustness of a first-order CATS controller is evaluated for different partitioned cases. It is shown that an adaptive compensation strategy is an effective approach for RTHS based on nine performance criteria due to its simple implementation and accuracy.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Signal Processing
- Civil and Structural Engineering
- Aerospace Engineering
- Mechanical Engineering
- Computer Science Applications