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Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy
Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy
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Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy
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Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy
Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy

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Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy
Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy
Journal Article

Robust speed and levitation control of high-speed trains using TSK type-2 fuzzy sliding mode strategy

2025
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Overview
High-speed trains are very sensitive due to their very high speed of movement, so the slightest defect or fault is not acceptable. This sensitivity necessitates the development of advanced and robust control strategies capable of handling dynamic uncertainties, nonlinearities, and external disturbances commonly present in high-speed rail systems. To achieve this, the control system must be very precise and eliminate the smallest errors. In this paper, a very precise nonlinear controller is designed by combining the TSK type-2 fuzzy system with the sliding mode control (SMC) method. The integration leverages the robustness of sliding mode control and the superior uncertainty modeling capability of TSK Type-2 fuzzy logic, aiming to overcome the limitations of conventional SMC and Type-1 fuzzy approaches. The TSK Type-2 fuzzy system can estimate sliding surfaces well and the control system will be very fast and accurate. In the simulation section, an attempt has been made to apply the parameters of a real train in order to evaluate it more accurately with the proposed control system. The results show the high efficiency of the proposed control system so that the RMSE of the control system reaches less than 1%. Compared to other existing control methods, the proposed controller demonstrates significant improvements in tracking accuracy, vibration reduction, and control effort minimization. Theoretical analysis based on Lyapunov stability further confirms the stability and reliability of the closed-loop system.