Interval Sliding Mode Observer Based Incipient Sensor Fault Detection with Application to a Traction Device in China Railway High-speed

This paper proposes an interval sliding mode observer (ISMO) and an incipient sensor faults detection method for a class of nonlinear control systems with observer unmatched uncertainties. The interval bounds for continuous nonlinear functions and new injection functions are constructed to design ISMOs. An incipient fault detection framework with newly designed residual and threshold generators is proposed. The detectability is then studied, and a set of sufficient detectable conditions are presented. Applications to an electrical traction device used in China Railway High-speed (CRH) are presented to verify the effectiveness of the proposed incipient sensor fault detection methodology

Incipient Fault Detection for Traction Motors of High-Speed Railways Using an Interval Sliding Mode Observer

This paper proposes a stator-winding incipient shorted-turn fault detection method for the traction motors used in China high-speed railways. Firstly, a mathematical description for incipient shorted-turn faults is given from the quantitative point of view to preset the fault detectability requirement. Then, an interval sliding mode observer is proposed to deal with uncertainties caused by measuring errors from motor speed sensors. The active robust residual generator and the corresponding passive robust threshold generator are proposed based on this particularly designed observer. Furthermore, design parameters are optimized to satisfy the fault detectability requirement. This developed technique is applied to an electrical traction motor to verify its effectiveness and practicability

Decoupled Fractional Super-Twisting Stabilization of Interconnected Mobile Robot Under Harsh Terrain Conditions

The four-wheel omnidirectional mobile robot usually suffers disturbed or unstable lateral motion under harsh terrain conditions (such as uneven or oiled ground). Generally for such a challenging situation, the lumped disturbances and interconnected states render available coupling solutions difficult to achieve demand-satisfied performance. This paper proposes a novel decoupled fractional super-twisting sliding mode control (FST-SMC) method by (i) constructing an inverse system-based decoupling to form a pseudolinear composition system; (ii) presenting an enhanced nominal sliding law for chattering mitigation and (iii) designing an unbiased multi-layer fuzzy estimator with gain-learning capacity to compensate for the lumped disturbances actively. Given that the identified disturbances can be directly reflected in the FST-SMC law, this method guarantees an accurate and robust control without causing gain overestimation. Theoretical analysis is offered to verify the asymptotic stability. Under harsh terrain conditions, experimental results validate the effectiveness of the proposed FST-SMC method