Simultaneous state and parameter estimation based actuator fault detection and diagnosis (FDD) for single-rotor unmanned helicopters (UHs) is investigated in this paper. A literature review of actuator FDD for UHs is given firstly. Based on actuator healthy coefficients (AHCs), which are introduced to represent actuator faults, a combined dynamic model is established with the augmented state co...

Planetary rovers operate in environments where human intervention is expensive, slow, unreliable, or impossible. It is therefore essential to monitor the behavior of these robots so that contingencies may be addressed before they result in catastrophic failures. This monitoring needs to be efficient since there is limited computational power available on rovers. We propose an efficient particle...

The multi-step prediction problem of chaotic time series with one sampling delay is investigated in this paper. The delay is considered to be random and is modelled by a binary white noise with values of zero or one, and these values indicate that the observation arrives on time or that it is delayed by one sampling time. Based on the original extended Kalman filtering (EKF) and the Unscented K...

The gradual decreasing capacity of lithium-ion batteries can serve as a health indicator for tracking the degradation of lithium-ion batteries. It is important to predict the capacity of a lithium-ion battery for future cycles to assess its health condition and remaining useful life (RUL). In this paper, a novel method is developed using unscented Kalman filter (UKF) with relevance vector regre...

Vehicle tracking in the field of intelligent transportation has received extensive attention recent years. Multi-sensor-based vehicle system is widely used some critical environments. However, actual scenes, observation error each sensor often different and time varying because environmental change channel difference. Therefore, this paper, we propose a multi-sensor interacted vehicle-tracking ...

Lithium-ion batteries (LIBs) are widely used as energy storage devices. Accurately estimating the state of charge (SOC) is critical for safe operation LIBs, but complex internal characteristics LIBs make this a difficult task. In study, an algorithm called BPNN-UKF, which combines backpropagation neural network (BPNN) and unscented Kalman filtering (UKF), proposed. First, fusion model construct...

An equivalent circuit model of dual polarization (DP) lithium battery was established according to the application characteristics under standby condition 5G base station. On basis model, recursive least square method with forgetting factor (RLS) used identify parameters. Finally, Unscented Kalman filtering (UKF) estimate SOC in real time identified The simulation and experimental results showe...

Global Navigation Satellite System (GNSS) has been widely utilized as a navigation solution for mobile vehicle, yet stand-alone GNSS is unable to achieve sufficient accuracy in some applications. For example, aquatic environment, the position of Unmanned Surface Vehicle (USV) affected by wind, current, and waves dynamics. In this case, integration Inertial Measurement Unit (IMU) an approach tha...

This paper addresses the problem of state estimation for nonlinear systems by means of the unscented Kalman filter (UKF). Compared to the traditional extended Kalman filter, the UKF does not require the local linearization of the system equations used in the propagation stage. Important results using the UKF have been reported recently but in every case the system equations used by the filter w...