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.
A fault detection, identification, estimation and state estimation (FDIESE) problem involves joint decision and estimation (JDE). Decision contains detection and identification, while estimation is for fault severeness and system state. Both detection and identification are highly coupled with estimation and a fault is identified after detection. To solve this problem, an approach named nested joint...
This paper presents an approach to fault detection, identification, and state estimation (FDISE) for a dynamic system with abrupt total or partial failures. FDISE includes both decision and estimation and they are highly coupled. Decision includes fault detection and identification (FDI), while estimation is for failure magnitude and system state. Correct FDI benefits estimation and accurate estimation...
Multi-target tracking (MTT) has been an important and challenging area of research in the past several decades. A number of algorithms for MTT have been proposed and related performance evaluation (PE) is also gaining more attention. However, these PE methods assume exact knowledge of the ground truth, which is far from the reality. In this paper we deal with the PE of MTT without knowing ground truth...
Due to the increased resolution capability of modern sensors, the assumption that the received measurement originated from a point source may be invalid. Thus extended target tracking becomes more and more important in many practical scenarios. A novel extended target model has been proposed that describes the target approximately using a star-convex shape. Although the star-convex model can model...
This paper considers a probabilistic approach to state estimation for discrete-time dynamic systems with unknown inputs. A variational Bayes method is proposed to approximate the marginal posterior distributions of system state and input. In order to reduce the computational complexity, the complete-data likelihoods of system from the exponential family are considered, and the conjugate prior distributions...
The state of some practical dynamic systems satisfies constraints, which can be utilized to improve the performance of state estimation. State estimation with nonlinear inequality constraints is a challenging problem. Projection methods are widely used to solve this problem. In this paper, a projection method is formulated as a special nonlinear function. Based on this formulation, unconstrained estimated...
A variable-structure multiple-model (VSMM) approach, named equivalent-model augmentation (EqMA), is proposed. Here the model set is augmented by a variable model intended to best match the unknown true mode. To fully utilize the information provided by model sequences, this variable model depends on the true mode at the previous time. Thus different previous models correspond to different augmenting...
This paper considers the problem of state estimation for a hybrid system with Markovian switching parameters which belong to a continuous space. A hybrid grid multiple model (HGMM) estimator is presented. The total model set for HGMM is the combination of a fixed coarse grid and an adaptive fine grid. Three practical algorithms in this scheme are developed. These algorithms are used for state estimation...
In this paper we propose an approach to detect, identify and estimate failures, including partial failures, in a dynamic system. The approach (IM/sup 3/L) uses the interacting multiple model (IMM) estimators to detect and identify total and partial failures and the maximum likelihood estimator (MLE) to estimate the extent of failure. It provides an effective and integrated framework for fault detection,...
The Interacting Multiple Model (IMM) algorithm has been shown to be one of the most cost-effective hybrid state estimation schemes. Its performance, however, could only be evaluated via expensive Monte-Carlo simulations. An effective approach to the performance evaluation without recourse to simulations is presented in this paper. This approach is based on a performance measure of hybrid nature in...
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.