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Real-time hybrid simulation (RTHS) is intended to serve as a technique able to conduct experiments when the behavior of the plant is not well understood, i.e., when deep uncertainties are present in the physical specimen. By combining strategies from robust control and adaptive control, this paper develops an adaptive sliding mode control (ASMC) system for uncertain control plants. The ASMC consists of a bounded-gain forgetting least-squares estimator and a sliding mode controller, aimed at estimating parameters of the control plant and eliminating the negative effects of estimation errors, respectively. The ASMC is evaluated by applying it to the benchmark control problem in RTHS, where the fifth-order control plant is reduced to a second-order control plant to facilitate the control system's design and execution. High performance and robustness are achieved with the adoption of ASMC. The results demonstrate that an effective ASMC can be designed based on a significantly simplified control plant, making it a potent control system for RTHS. K E Y W O R D Sadaptive control, model uncertainties, real-time hybrid simulation, robust control, sliding mode control | INTRODUCTIONReal-time hybrid simulation (RTHS) is a cyber-physical technique to conduct experimental studies of large-scale and complex structures subject to dynamic loading. 1 In RTHS, the structure under investigation is divided into the numerical substructure-computational model simulated in a computer and the physical substructure-experimental specimen(s). The numerical substructure should contain the majority or larger part of the structure. It is typically assumed to be well understood and can be numerically modeled precisely, while the rest of structure, normally individual elements(s) or device(s) inside of the structure, e.g., a damper, is treated as a physical substructure and is