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The paper is aimed to control design of uncertain linear multivariable plants in conditions of quantized output and external disturbances. Control law synthesis is based on the consecutive compensator method. Obtained algorithm provides tracking error of quantized output for the reference signal with fixed accuracy. Accuracy range depends on the quantization step and disturbances bounds. There are...
Based on new results on ideal adaptive sliding mode control (ASMC) design for nonlinear systems with uncertainties discussed in Part I of the present contribution, we extend the new designs to the real case in this paper (Part II) by using boundary layer method and filtered rate of the sliding variable. These modifications are proposed to enhance accuracy without overestimation of the uncertainty...
The switching power supply is widely used in many applications, but due to its complexity, it is difficult to solve the fault diagnosis problems by the traditional fault diagnosis methods. And many algorithms based on data driven, offer a tool to deal with these problems without any preliminary or additional information. However, the incomplete data (or missing values) deteriorate their performance...
This paper presents a detailed comparison of the most significant methods developed to compute lower bounds on the structured singular value. The objective is to characterize the behavior of these robustness analysis tools on the basis of a common framework constituted by a wide set of various real-world applications.
Motivated by the complexity of solving convex scenario problems in one-shot, two new algorithms for the sequential solution of sampled convex optimization problems are presented, for full constraint satisfaction and partial constraint satisfaction, respectively. A rigorous analysis of the theoretical properties of the algorithms is provided, and the related sample complexity is derived. Extensive...
In this paper, we propose a procedure for computing the dissimilarity measure of finite general type-2 fuzzy sets, represented as sequences of vertical slices. Through representing general type-2 fuzzy sets as a sequence of objects, we compute their overall dissimilarity value using suited matching algorithms for generalized sequences. The evaluation of the proposed matching algorithm is performed...
This paper proposes a novel way of matching general type-2 fuzzy sets using a sequence-based approach. General sequences are defined as an ordered list of objects, which are called events. In our contribution, an event of the sequenced type-2 fuzzy set is defined as the footprint of uncertainty of a specific α-plane. Suited matching algorithms for generalized sequences can be applied to this new interpretation,...
In order to compare the classification accuracies and performance differences between traditional and probability-based decision tree classifiers, and come to understand those algorithms, which aim to improve construction efficiency of probability-based decision trees, mentioned in "Decisions Trees for Uncertain Data", this paper tested several algorithms, named AVG, UDT, UDT-BP, UDT-LP,...
The use of Prognostics and Health Management (PHM) technologies has recently received an increased amount of interest from many industries. For deployment of a PHM system successfully, A key step is prognosis certification. This calls for a set of performance metrics that not only evaluate key aspects of predicting into the future but also integrate notions from practical aspects such as reliability,...
To solve problems in data-driven fault prognostic study such as prediction uncertainty management, multiple fault features and on-line prognostics, an algorithm based on multivariate relevance vector machine (MRVM) is presented. It extends the existing time series iterative multi-step prediction to the application with multiple fault features by matrix partitioning technique. For on-line application,...
In this paper, we present a randomized strategy for design under uncertainty. The main contribution is to provide a general class of sequential algorithms which satisfy the required specifications using probabilistic validation. At each iteration of the sequential algorithm, a candidate solution is probabilistically validated by means of a set of randomly generated uncertainty samples. The idea of...
A proper discretization 1 of numerical attributes is of paramount importance on applications of data mining and machine learning. In the classical discretization algorithm based on information entropy, the importance of the breakpoints is measured by the decrement of the uncertainty level in a decision table. In this paper, a novel discretization algorithm based on positive domain is proposed. It...
For the sake of measuring fuzzy uncertainty and rough uncertainty of real datasets, the fuzzy rough membership function (FRMF) defined in fuzzy rough set is introduced. A new fuzzy rough neural network (FRNN) is constructed based on neural network implementation of FRMF. FRNN has the merits of quick learning and good classification performance. And then a new neural network feature selection algorithm...
This paper provides root finding methods for the centroid computation of interval type-2 fuzzy sets and general type-2 fuzzy sets with linear secondary membership function. When the FOUs of the type-2 fuzzy sets are provided, the centroid computation methods in this paper is accurate and computational efficient, which provide new methods for the type-2 fuzzy systems computation.
Active learning methods seek to reduce the number of labeled instances needed to train an effective classifier. Most current methods are myopic, i.e. select a single unlabelled sample to label at a time. The batch-mode active learning methods, on the other hand, typically select top N unlabeled samples with maximum score. Such selected samples often cannot guarantee the learner's performance. In this...
The DEM of Seabed is the core and foundation in the analysis of chart. In this paper a method of constructing the DEM of seabed based on uncertainty is proposed. Firstly, according to the uncertainty of the soundings data, the distributing law is explained and the interpolation model is constructed. Secondly, according to propagating law of the uncertainty, the DEM of Seabed based on uncertainty of...
The centroid of a general type-2 fuzzy set (T2 FS) Ã can be obtained by taking the union of the centroids of all the α-planes (each raised to level α) of Ã. Karnik-Mendel (KM) or the Enhanced Karnik-Mendel (EKM) algorithms are used for computing the centroid of each α-plane. The iterative features in KM/EKM algorithms can be time-consuming, especially when the algorithms have to be repeated for...
The main purpose of the paper is to present sophisticated means to implement Q-guidance scheme in satellite injection missions. Optimality and simplicity of Q-guidance approach makes it appropriate for practical settings of a wide range of launch systems. Calculation of required velocity as a fundamental and inherent concept of Q-guidance implementation for orbital injection missions has been proposed...
In a distributed network system, data collection devices (e.g., sensors) may operate on fuzzy inputs, thereby generating results that possibly deviate from the reference datum in physical world being sensed. The extent of deviation and the time it takes to compute an output result (i.e., inaccuracy and timeliness of event notification) depend on the number of orthogonal information elements, i.e.,...
Firstly, by preprocessing classification rule, we account distinct outlier attributes subspace of the rules about classification rules attributes, then it uses attribute weight vector to calculate weighted distance; secondly, it analyzes subspace outlier influence factor of weighted neighborhood area; finally, we creates frequent matching Sub-Set by comparing with subspace outlier influence factor...
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