Adaptive model reference control method for real-time hybrid simulation

摘要

The real-time hybrid simulation (RTHS) methodology is an experimental technique involving substructuring of a full-scale experiment into numerical and experimental partitions. It offers a cost-effective solution and is highly practical in confined laboratory settings. Successful implementation of RTHS is dependent on successful tracking control and robustness of the hybrid simulation loop. This paper addresses the benchmark problem in RTHS, which intends to assess available actuator tracking controllers and other advanced computational frameworks for successful RTHS implementation. Most existing control algorithms tend to instability when faced with challenges of plant uncertainty and nonlinearity. Stability has been at odds with excellent tracking, where controllers with rigorous tracking have had poor stability performance and robust controllers have had poor tracking performance. This paper introduces an Adaptive Model Reference Control (aMRC) method for displacement tracking of actuators, which offers an excellent tracking ability and maintains robustness under unmodeled dynamics and uncertainties. The proposed controller is composed of feedforward and feedback links, a reference model, and an adaptation law. The tracking and robustness performance of the proposed algorithm are evaluated through a numerical RTHS of the three-story steel frame building described in the benchmark problem statement. The benchmark problem defines different mass and damping configurations while partitioning the structure. Additionally, the experimental substructure is made uncertain by modeling several actuator and stiffness parameters probabilistically, per the benchmark problem. The performance of the proposed controller is compared to several commonly employed control techniques and assessed using the evaluation criteria described in the benchmark problem statement. The results show that the proposed aMRC algorithm tracks the desired reference signal well while maintaining robustness.