Fault prognosis is mainly referred to the estimation of the operating time before a failure
occurs, which is vital for ensuring the stability, safety and long lifetime of degrading industrial …

This paper presents a data-driven prognostic framework for rolling-element bearings
(REBs). This framework infers a bearing's health index by defining a degree-of …

This article develops a unified framework to design fuzzy-model-based observers of general
nonlinear systems for both discrete-time and continuous-time cases. This observer problem …

A novel robust control design is proposed for aircraft engines. The engine is modeled as an
uncertain dynamic system, whose uncertainty may be (possibly fast) time-varying. The …

This paper proposes a novel Error Based Evolving Takagi–Sugeno Fuzzy Model (EBeTS)
and a new data-driven approach to fault prognostics based on that fuzzy model. The …

In recent years, the deep neural network technology has developed rapidly and has been
effective in processing and analyzing images, videos, sounds and many other aspects …

Linear regression is the use of linear functions to model the relationship between a
dependent variable and one or more independent variables. Linear regression models have …

Fault detection (FD) for traction systems is one of the active topics in the railway and
academia because it is the initial step for the running reliability and safety of high-speed …

For maneuvering target tracking, a novel adaptive variable structure interactive multiple
model filtering and smoothing (AVSIMMFS) algorithm is proposed in this paper. Firstly, an …

The extended Kalman filter (EKF) as a primary integration scheme has been applied in the
Global Positioning System (GPS) and inertial navigation system (INS) integrated system …