An adaptive sliding mode control system and its application to real-time hybrid simulation

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.