This study tackles the problem of fault‐tolerant attitude estimation for small satellites. A probabilistic adaptive technique is presented for the multiplicative extended Kalman filter (MEKF) algorithm that is used in attitude estimation. The ...

This study presents a probabilistic adaptive Kalman filter for small satellite attitude determination, demonstrating superior fault tolerance by effectively correcting sensor faults and outperforming conventional and other adaptive filters. image image

This paper presents a fixed‐time state observer‐based robust adaptive neural fault‐tolerant control (RANFTC) for attitude and altitude tracking and control of quadrotor unmanned aerial vehicles (UAVs), considering multiple actuator faults, ...

This article presents a fixed‐time state observer‐based robust adaptive neural fault‐tolerant control for attitude and altitude tracking and control of quadrotor unmanned aerial vehicles, addressing multiple actuator faults, model uncertainty, and unknown ...

In practical sensor networks, sensor nodes may operate with different sampling periods and initial sampling time instants, and their observations may also be nonuniform. Unfortunately, the research on distributed state estimation problems over ...

image image Actually, in sensor networks, different sensor nodes may operate with different sampling periods and initial sampling time instants, and their observations may also be non‐uniform. To deal with this problem, this paper contributes by ...

This article proposes the design of the resolution‐dependent variance‐constrained state estimation (RDVCSE) algorithm for a class of time‐varying nonlinear coupled complex networks (TVNCCNs) with stochastic communication and correlated noises. ...

The resolution‐dependent state estimation algorithm subject to stochastic communication. image image

In this paper, an indirect filtering fault‐tolerant control method is proposed for interconnected time‐delay systems with multiple sensor and actuator faults. As is well known, directly utilizing the state information obtained from sensors with ...

In this article, we study parameter estimation problems for fractional commensurate Hammerstein systems utilizing the conformable fractional derivative. Two algorithms are investigated: first, the Poisson moment functions (PMF) method, aiming to ...

Under the influence of sensor saturation and packet dropout, this paper is concerned with the fault detection (FD) problem for a class of nonlinear systems with two additive time‐varying delay components. In the addressed measurement model, the ...

Aiming at the problem that distributed secondary control is vulnerable to FDI attacks in DC microgrid, which affects the stability of the system, and the problems of communication redundancy and energy loss in traditional distributed secondary ...

In this paper, a modified consensus protocol algorithm is proposed for controlling a group of identical unmanned aerial vehicles (UAVs), which have been subjected to interfering signals during coordinate information exchange, using an unknown ...

In practical applications, many processes have nonlinear characteristics that require nonlinear models for accurate description. However, constructing such models and determining their parameters are a challenging task. This article explores ...

We consider the problem of stochastic identification of multiple sinusoids from intermittently missing measurements of superimposed signal. An alternate problem formulation is presented as estimation of amplitude and frequency of the sinusoids ...

In this article, an event‐triggered recursive filtering problem is studied for a class of nonlinear multi‐rate systems (MRSs) with random transmission delays (RTDs). The RTDs are described by utilizing random variables with a known probability ...

Since bearing defects usually occur which threaten the stable operation of the machinery, bearing fault detection is of great importance. However, the bearing fault signals inevitably exhibit strong interference components due to the complex ...

This article investigates the robust steady‐state matrix‐weighted fusion (MWF) filtering problem for multisensor multichannel autoregressive (AR) signal with multiple uncertainties, which can be transformed into the state estimation problems in the ...

Stochastic resonance can detect weak periodic signals from strong background noise without loss of signal energy. However, the classical bistable stochastic resonance has the inherent output saturation defect, which limits the detection ...

This article investigates the event‐triggered Kalman consensus filtering (ET‐KCF) problem for distributed sensor networks with intermittent observations. First, a novel ET consensus filtering structure is designed for sensor networks with ...

This paper studies the problem of parameter estimation for the multifrequency sine signals, which have multiple characteristic parameters such as the amplitudes, phases, and frequencies. It is noted that the signal output is nonlinear with respect ...

Electrocardiogram (ECG) signal transmission and monitoring plays a paramount role in long‐term cardiac monitoring and analysis to provide remote health care in time, especially for the postoperative people and people in remote areas. The accuracy ...

An adaptive integrated navigation system, consisting of barometric altimeter (Baro) and GPS, is presented. The integration is achieved by using an adaptive data fusion algorithm with the filter gain correction. Proposed adaptive data fusion ...

Cylinder pressure signal provides key feedback information that allows for several engine monitoring and control capabilities. During the last few years, the use of cylinder pressure traces for advanced combustion strategies has become the focus ...