New Insights on Robust Control of Tilting Trains with Combined Uncertainty and Performance Constraints

Fazilah Hassan (), Argyrios Zolotas () and George Halikias
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Fazilah Hassan: School of Electrical Engineering, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia
Argyrios Zolotas: Centre for Autonomous and Cyber-Physical Systems, SATM, Cranfield University, Cranfield MK43 0AL, UK
George Halikias: Department of Mathematics, National and Kapodistrian University of Athens, University Campus, 15784 Athens, Greece

Mathematics, 2023, vol. 11, issue 14, 1-19

Abstract: A rigorous study on optimized robust control is presented for non-preview (nulling-type) high-speed tilting rail vehicles. The scheme utilizes sensors on the vehicle’s body, contrary to that of preview tilt (which uses prior rail track information). Tilt with preview is the industrial norm nowadays but is a complex scheme (both in terms of inter-vehicle signal connections and when it comes to straightforward fault detection). Non-preview tilt is simple (as it essentially involves an SISO control structure) and more effective in terms of (the localization of) failure detection. However, the non-preview tilt scheme suffers from performance limitations due to non-minimum-phase zeros in the design model (due to the compound effect of the suspension dynamic interaction and sensor combination used for feedback control) and presents a challenging control design problem. We proposed an optimized robust control design offering a highly improved non-preview tilt performance via a twofold model representation, i.e., (i) using the non-minimum phase design model and (ii) proposing a factorized design model version with the non-minimum phase characteristics treated as uncertainty. The impact of the designed controllers on tilt performance deterministic (curving acceleration response) and stochastic (ride quality) trade-off was methodically investigated. Nonlinear optimization was employed to facilitate fine weight selection given the importance of the ride quality as a bounded constraint in the design process.

Keywords: tilting trains; robust control; optimization; mixed sensitivity; robust performance; active suspensions (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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