摘要：Abstract: Modern pantograph current collectors for high-speed trains are mechatronic systems that are increasingly equipped with active control to maximize their dynamic performance. To realize a high-quality contact, decrease wear, and increase speed, it is necessary to use high-fidelity co-simulation and hardware-in-the-loop (HiL) testing tools, as well as modern model-based control (MBC) concepts. In all these areas, efficient, real-time-capable and accurate models of the pantograph dynamics are required. This paper proposes two different real-time-capable nonlinear pantograph models based on the local model network (LMN) methodology, intended for utilization in co-simulation and control design. They are identifiable by measurement data and applicable for different pantograph geometries. The proposed model structures attain significant improvements in accuracy compared to classical models via global linearization, and they are highly computationally efficient.
关键词：KeywordsNonlinear modelingpantographreal-time capabilitylocal linear neuro-fuzzy networkMIMO systemsubspace identification
