A robust recursive speed tracking estimation for subway trains under uncertain bounded disturbance

This article investigates the speed tracking estimation problem for the subway system under uncertain bounded disturbance. Firstly, the nonlinear running model of the train with dynamic descriptions is formulated, which contains traction/braking force, basic resistance, gradient, and uncertain disturbance under different conditions. By modeling the linearization error as uncertain parameters, a convex optimization problem of Kalman-like nonlinear estimator is established. Then, a robust speed tracking method is designed based on linear matrix inequalities and bounded recursive optimization idea, and the sufficient conditions to ensure the bounded stability of the nonlinear estimator are derived. Therefore, an effective solution to the stability problem of the designed nonlinear estimator with unknown disturbance statistical characteristics is given. Finally, the actual operational data of Ningbo Metro Line 7 is employed to verify the effectiveness of the proposed method.