Post by Altan Onat

Our article, “Novel swarm intelligence-based multiple models approaches for parameter estimation: Application to a railway vehicle system with traction”, has just been published in Ain Shams Engineering Journal (Elsevier). In this study, together with my colleague Bekir Tuna Kayaalp, we propose new swarm intelligence-inspired approaches for multiple-model parameter estimation — particularly designed for systems with noisy measurements and model discrepancies. These approaches are an extension of our earlier work, “A Novel Methodology for Dynamic Weigh in Motion System for Railway Vehicles with Traction”, published in IEEE Transactions on Vehicular Technology (2019). By applying the new methods to a railway vehicle system under traction, we demonstrate improved estimation accuracy while reducing the need for additional tuning. We are also grateful to our colleagues, doc. Ing. Petr Voltr and doc. Ing. Michael Lata, from the University of Pardubice, CZ. You can read the full paper here 👉 https://lnkd.in/dvXdh_6K