The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Acoustic sensor networks (ASNs) have been identified as a promising technology to monitor and explore the underwater resources. Most applications of ASNs are required to track an underwater target in an accurate and efficient manner. However, the resource-constrained characteristics on acoustic communication makes it challenging to achieve the tracking task. In this paper, we are concerned with underwater...
For ARMAX models, a Latest-Estimation Based Hierarchical Recursive Extended Least Squares algorithm is presented in this paper. The basic idea is to make full use of the latest estimation, and combine this with the hierarchical idea. In the proposed algorithm, the estimates of the white noise information vector is updated by using the latest estimation. The convergence performance of the proposed...
This paper proposes a parameter estimator for four-wheel-independently driven electric (4 WID) vehicle with in-wheel motors. The mass and location of payload have great impacts on the stability and maneuverability of lightweight vehicles (LWVs). Fast, effective and real-time parameter estimator can make the existing controller adjust the changed parameter caused by additional payload. The proposed...
This paper studies the interval estimation problem of reliability parameters of binomial distribution, in the case of zero-failure data, using the method of two-sided M-Bayesian credible limit. It proves the hypothesis that was provided by Han [1]: two-sided M-Bayesian credible limits is superior to the corresponding two-sided classical confidence limits when estimation reliability derived from binomial...
A robust diffusion adaptive filtering algorithm, called the diffusion recursive least lp-norm (DRLP), is developed for distributed estimation over network. The new algorithm aims at recursively minimizing the lp-norm of error, and can offer a more stable and robust solution than traditional adaptive filtering schemes based on minimization of the squared error, such as the diffusion recursive least...
This paper studies the event-triggered control problem for continuous-time systems subject to external disturbances. In particular, we consider continuous-time systems with bounded external disturbances. To overcome infinitely fast sampling caused by the disturbance, a combination of time-based trigger and event-based trigger is proposed, and an estimation of the magnitude of the external disturbance...
This paper proposes an H∞ polytopic filter design for a nonlinear system. Based on the polytopic approximation of the nonlinear system, the polytopic filter design is converted into a group of linear matrix inequalities (LMIs) so that the polytopic filter parameters can be effectively acquired by numerical convex optimization algorithms. At this stage, the tensor product (TP) model transformation...
Due to the unknown or not monitored excitations on the structure, a novel General Extended Kalman filter with unknown inputs (GEKF-UI) was proposed to successfully estimate the structural parameters and the unknown excitations (inputs) simultaneously. The proposed GEKF-UI gives an analytical EKF solution dealing with the more general measurement scenarios with the existing EKF methods as its special...
The reachable set estimation problem of discrete-time Markovian jump systems with time-varying delay is concerned with in this note. By utilizing Lyapunov theory and reciprocally convex combination approach, a sufficient reachable set estimation condition is proposed in terms of linear matrix inequalities (LMIs). A numerical example is provided to demonstrate the workability of the proposed results.
In this paper we present a new method of reconstructing an image that undergoes a spatially invariant blurring process and is corrupted by noise. The methodology is based on a theory of multidimensional moment problems with rationality constraints. This can be seen as generalized spectral estimation with a finiteness condition, which in turn can be considered a problem in system identification. With...
This paper addresses a difficult problem of designing a control approach with simple structure to perform attitude tracking maneuver for rigid satellites. The satellite is subject to disturbance torques and uncertain inertia parameters. An observer-based estimation law is firstly proposed to reconstruct the uncertain dynamics. It is shown that such estimation can be achieved with zero estimation error...
For the descriptor system with unknown noise variances, the self-tuning full-order Kalman filter with self-tuning descriptor Riccati equation is presented. Firstly, the fused estimates of these unknown noise variances can be obtained by the correlation function method. Then, substituting these fused estimates into the recursive Kalman filter with descriptor Riccati equation yields the self-tuning...
This paper studies the problem of distributed estimation for discrete-time nonlinear systems with Gaussian mixture noise. A merge-fusion-split strategy has been proposed to develop a distributed Gaussian sum filter (GSF) over a sensor network. In the proposed filter, the GSF is implemented for each sensor to generate local estimates and the local estimates of Gaussian components are merged as a single...
This paper addresses the problem of estimating states and parameters of chaotic memristive systems with single measurable variable. Based on the conventional extended Kalman filter, we present two new strategies based on the joint extended Kalman filter and dual extended Kalman filter. Then, the two kinds of filters are employed to estimate the states and parameters of chaotic memristive systems....
This note is concerned with the linear estimation problems for discrete-time systems where the measurements are subject to random time delay and packet drop. Due to the time stamping being assumed to be unavailable in this paper, the estimation problems for such systems are very difficult because the information of the received measurements is not exactly known in most cases. To overcome the difficulty...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.