Adaptive model predictive control for actuation dynamics compensation in real-time hybrid simulation

Hybrid simulation is used to obtain the dynamic response of a system whose components consist physical and numerical substructures. The coupling these substructures achieved by actuation systems, which are commanded in closed-loop control setting. To ensure high fidelity such hybrid simulations, performing them real-time necessary. However, poses challenges since inherent dynamics introduce time delays, thus modifying investigated system. Therefore, tracking controller required adequately compensate for delays. In this study, novel proposed compensation simulations. It based on adaptive model predictive control, linear time-varying Kalman filter, identification algorithm. Within latter, auto-regressive exogenous polynomial models identified estimate changing plant dynamics. A parametric virtual case encompassing motorcycle, validate performance robustness controller. Results demonstrate effectiveness