Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
This note focuses on robust adaptive controller design for Hammerstein systems with symmetric dead-zone nonlinearity and bounded noise. A modified control law is proposed to compensate dead-zone nonlinearity and a new recursive estimator with a nonnegative data weighting is presented to deal with bounded noise. From convergence properties and global stability analysis, we show that parameter estimation...
This paper considers the problem of global output feedback control for a class of nonlinear systems with inverse dynamics. The main contribution of paper is that: For the inverse dynamics with uncertain ISS/iISS supply rates, we construct a reduced-order observer-based output feedback controller, which drives the output of system to zero and maintain other closed-loop signals bounded. Finally, a simulation...
In the paper, a regularized correntropy criterion (RCC) for radial basis function neural network (RBFNN) is proposed. In RCC, the Gaussian kernel function is used to replace the Eculidean norm of the sum-squared-error (SSE) criterion. Replacing SSE by RCC can improve the anti-noise ability of RBFNN. Moreover, the optimal weights and the optimal bias terms can be iteratively obtained by the half-quadratic...
This paper studies the mean square and almost sure consensus of discrete-time linear multi-agent systems with communication noises under Markovian switching topologies. By a sophisticated stochastic-approximation type protocol, the closed-loop dynamics of this linear multi-agent system can be transformed into a discrete-time first-order integral multi-agent system. It is proved that if all roots of...
This paper solves the problem of time synchronization in wireless sensor networks (WSNs) with noise. The consensus based approach is an improved average value based protocol. This algorithm, compared with the existing consensus-based synchronization approach, has the advantage of being totally distributed, asynchronous and robust to process and measurement noise. The main idea of this algorithm is...
Information fusion for nonlinear systems is one of the challenging topics in target tracking recently. Aiming at a kind of multi-sensor target tracking systems with correations between process and measurement noises, we study the design of a decentralized fusion algorithm based on the unscented strong tracking filter with correlated noises (USTF-CN). Firstly, the information form of USTF with correlated...
To improve Maneuver Target Tracking Algorithm, The multi-model intelligent input estimating method based on fuzzy logic is proposed. A fuzzy inference system is constructed with the input of the residual of observation and the residual variation. Then we could get the real-time estimate of the maneuver input of the model according to the output of the system. The algorithm is optimized by the parameter...
A saturation allowed scheduled anti-windup design method is proposed in this paper for the linear systems subject to input saturation. We introduced the scheduled controller design method into the anti-windup scheme, in which a family of controllers are designed. These controllers are activated depending on the response of the system, rather than only considering the worst noise case off-line. Also,...
Sensor localization is a basic and important task of wireless sensor networks, and abundant localization algorithms have been proposed based on various ranging techniques, including time-of-arrival (TOA), time-difference-of-arrival (TDOA), received signal strength (RSS), angle-of-arrival (AOA) and etc. The accuracy of these ranging techniques rely on the line-of-sight (LOS) propagation of signals,...
This paper studies the synchronization problem of multi-agent systems with nonlinear dynamics in mean square. It is supposed that the measurement of relative-state is disturbed. For the nonlinear multi-agent systems, we show that the conventional consensus protocols are robust against the measurement noises which are dependent to the relative-state. Simulations are provided to demonstrate the theoretical...
Standard Kalman Filtering leads to divergence because of inaccurate system model and noise statistic. Researchers have taken relative studies about Kalman filtering optimization method. But now most studies are based on applications, such as integrated navigation system, so most of these methods are lack of general applicability. This paper starts from innovation-based adaptive estimation (IAE) filtering...
This paper presents slosh control within a container which represents an underactuated system. The dynamics of the system is highly coupled and non-linear. The major difficulty is in slosh state measurement. Hence an Output-feedback control is proposed. The non-linear sliding surface is a function of only measurable output variables. A robust exact Levant differentiator is designed for estimating...
In semiconductor manufacturing, it is important to produce multiple products on the same equipment to enhance the overall equipment effectiveness so as to improve the productivity. However, the “high-mix” production is difficult to control due to the time-varying model. To address this problem, an adaptive exponentially weighted moving average (EWMA) control method of which the core content is online...
This article uses the novelty and applicability of adaptive genetic algorithms for the development of advanced digital radio frequency memory jammer technology uses radar CFAR detection algorithm. As a major result, demonstrates how adaptive genetic algorithms can produce effective single-resistant interference. This is an important attribute when interference uncertain radar detection algorithms...
A non-destructive detection system based on machine vision was designed for identifying the fertility of eggs prior to virus cultivation. Specific imaging system and detection algorithm were presented. A method based on smallest univalve segment assimilating nucleus was introduced to distinguish the high-brightness speckle noise pixels in egg images since the high transmittance of holes in eggshell...
A robust tracking algorithm based on the particle filter with multi-cue adaptive fusion is proposed which can overcome the shortcoming of single visual cue in complex environments. The color and the texture based on the discrete wavelet transform (DWT) are used to describe the tracking target. The weights are adaptively adjusted using the democratic integration according to the current tracking situations,...
Brain disease is one of common diseases that threaten human health, which is becoming one of hot researches in society and medical profession. After a variety of image segmentation methods in the brain MR image segmentation are studied, it is found that FCM algorithm and SVM algorithm have a lot of advantages and good application prospection. Then a combination of unsupervised classification algorithm...
This paper studies the detectability of discrete-time stochastic linear systems with Markovian jump and multiplicative noises. An equivalent definition of the weak detectability for discrete-time stochastic linear systems will be discussed. And we show that the weak detectability has invariance under the linear output feedback.
Image super resolution (SR) reconstruction technique is receiving increasing attention from the image processing community, and it has been widely used in many applications such as remote sensing image, medical image, video surveillance and high definition television. The essential of image SR reconstruction technique is how to produce a clearly high resolution (HR) image from the information of one...
The Probability Hypothesis Density (PHD) filter is a more tractable alternative to the Random Finite Set (RFS) based optimal multitarget Bayes recursion. In this paper, a matrix reformulation of the Gaussian Mixture PHD (GM-PHD) filter is introduced. Thus a new multisensor GM-PHD filter is constructed based on the matrix reformulation. Simulation results show it can be used in some applications when...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.