Uncertainty appearing in datasets (stochastic, linguistic, of measurements, etc.), if not handled properly, may negatively affect information analysis or retrieval procedures. One of possible methods of dealing with uncertain (rare, strange, unexampled) data is to treat them as “outliers” or “exceptions”. Among different definitions and algorithms for detecting outliers, we are especially interested

In this paper, an observer-based adaptive fuzzy tracking control is considered for a class of strict-feedback nonlinear systems. The nonlinear functions and unmeasured states in the system are estimated by means of fuzzy logic systems and fuzzy state observers, respectively. In addition, the tan-type barrier Lyapunov specifies that the tracking error is limited to a given area. An improved event-triggered

This paper presents a path-following-based design for guaranteed cost control of a class of nonlinear systems represented by polynomial fuzzy systems. First, this paper proposes a polynomial Lyapunov function approach to guaranteed cost control for the feedback system consisting of a polynomial fuzzy system and a polynomial fuzzy controller. In particular, we introduce a new type of polynomial fuzzy

As a complex process, wireless optical communication of autonomous underwater vehicles (AUVs) is particularly challenging in the complex communication environment. Therefore, the existing control or denoise systems show some limitations for communication system of multi-AUV. It is still difficult to balance between the complexity of underwater environment and the performance of reality or estimation

In this paper, the synchronization problem of complex networks using fuzzy-based impulsive control is discussed. Synchronization problem is considered for networks with switching topologies. Also, each node of the networks has a time-varying chaotic dynamic. Based on the Takagi–Sugeno fuzzy model, a new representation of a complex network is presented. Using impulsive control theory, a new controller

Autonomous underwater vehicle (AUV) plays an important role in ocean research and exploration. The underwater environment has a great influence on AUV control and human–robot interaction, since underwater environment is highly dynamic with unpredictable fluctuation of water flow, high pressure and light attenuation. The traditional control model contains a large number of parameters, which is not effective

This paper considers the leader-following consensus problem for linear multi-agent systems (MASs) with actuator faults, matched unknown nonlinearity and non-identifiable uncertainty under switching network topology for studying. A novel distributed switching fault-tolerant controller is established by approximating the nonlinear dynamics using a fuzzy logic system and by developing adaptive update

Fuzzy addition is one of the operations widely used in the application of fuzzy systems. The analytical and closed form expressions of the fuzzy additions of the generalized fuzzy numbers and the interval type 2 fuzzy numbers (IT2FS) are developed. The generalized fuzzy numbers is a non-flat and subnormal fuzzy number with different left and right shape functions. Classical fuzzy operations based on

In view of the fact that most clustering algorithms cannot solve the clustering problem about samples with uncertain information, according to the theory of fuzzy sets and probability, we define the fuzzy-probability binary measure space and triangular fuzzy normal random variables firstly, and then combine the advantages of k-means algorithm, such as simple principle, few parameters, fast convergence

The intense competition of global markets stimulates a significant change in the way products are designed, manufactured, and delivered. Such a situation is forcing companies to consider the use of new tools to support this decision process. This paper describes an agent-based system implementing a novel consumer-based fuzzy multicriteria methodology to support the design of new products. It argues

Unlike other fuzzy modellings, probabilistic fuzzy sets can reflect clearly the importance of different numerical values. In group decision-making (GDM) problems, it is quite common for decision-makers (DMs) to elicit their knowledge with probabilistic hesitant fuzzy preference relations (PHFPRs), in which consistency adjustment and alternatives’ weight vector determination play a key role in the decision-making

This paper focuses on using nanofluid (graphene)/ultrasonic atomization minimum quantity lubrication (MQL) in micromilling for SKH-9 high-speed steel. Utilizing the special properties of graphene, which has excellent thermal conductivity, it is found that it successfully lowers the cutting temperature generated during processing, reduces tool wear, and improves the quality of micromilling products

Transshipment problems are special type of transportation problems in which goods are transported from a source to a destination through various intermediate nodes (sources/destinations), possibly to change the modes of transportation or consolidation of smaller shipments into larger or deconsolidation of shipments. These problems have found great applications in the era of e-commerce. The formulation

This paper purpose a structural design decision model by using service blueprint, failure mode effect analysis (FMEA), Fuzzy method, and the theory of inventive problem solving (TRIZ). In “service process analysis” stage, the service blueprint approach is used to analyze the potential service failure points in the service process. Then, FMEA is employed to diagnose the possible causes and effects of

Most patients have more than one disease, and these diseases are able to affect one another. In modern medicine, the etiology and pathophysiology of diseases are well known in detail. However, inter-disease relationships are still mysterious. Physicians’ knowledge and experience have great importance in such a multi-criteria case. Because medical doctors in internal medicine clinics deal with large

With the increasing use of wireless terminals, wireless sensor networks (WSNs) have received significant attention owing to their wide usage in monitoring harsh environments, crucial surveillance and security applications, and other real-life applications. Sensor nodes in operation are equipped with batteries that are not rechargeable in most of the cases. Attaining the lifetime maximization of these

This paper presents an intelligent adaptive proportional-integral-derivative (PID) control method using fuzzy broad learning system (FBLS) and investigates how the method can be applied to control a tool-grinding servo control (TGSC) system. Due to accuracy, quality and geometric errors which are often difficult to capture the dynamics of the controlled plants or systems, fixed-gain PID controllers

In this study, an adaptive fuzzy output tracking control scheme is proposed for uncertain strict-feedback systems with unknown control directions. Nussbaum-type functions are designed, with which the effects of multiple unknown control directions can be handled. Compared with the existing Nussbaum-type functions dealing with the same problem, the proposed Nussbaum-type functions have smaller amplitudes

This paper proposes a novel robust model-free adaptive interval type-2 fuzzy sliding mode control (MF-AIT2FSMC) for the proton exchange membrane fuel cell (PEMFC) system using nonlinear disturbance observer. The main control objective is to adjust the oxygen stoichiometry at its reference trajectory under load disturbances and parameter uncertainties, to avert the oxygen starvation problem and to obtain

Hospitals’ daily operations have become increasingly dependent on medical devices. However, the occurrence of faults is inevitable. Therefore, it is crucial for hospitals to make timely fault diagnoses and enact the corresponding measures and improvements. This paper proposes a novel concept lattice method for the intelligent diagnosis of medical device faults. To minimize the influence of uncertain

The current work has proposed an approach to the controller design of a fuzzy non-singular terminal sliding mode (NTSM) for a type of planar systems with input saturation. On the basis of a modified version of NTSM, a category of saturated NTSM controller is first constructed to ensure that the states can reach the sliding surface and finite-time converge to the origin. On this basis, a fuzzy logic

In this paper, we present a fuzzy PID control system as a combination of a fuzzy PID controller and a fuzzy control process, which is represented by a fuzzy control differential equation in linear form. We use the concepts of the generalized Hukuhara differentiability and the fuzzy integral of fuzzy-valued functions to study some qualitative properties for this system in the space of fuzzy numbers

For diabetes mellitus (DM), the technology of blood glucose monitoring provides detection information for patients and helps sufferers to ameliorate bad states. Management rules and intervention measures, which are consistent with blood glucose situation, help to control blood glucose stability, establish a healthy lifestyle, and prevent the occurrence of DM complications. Formulating effective rules

This paper is concerned with the problem of output feedback control for continuous-time T–S fuzzy systems. The aim is to reduce the conservatism of finding output feedback controller design conditions based on the Lyapunov function which depends on membership functions. Firstly, in order to improve the existing results, a new approach to bound the time derivatives of the membership functions is proposed

In this paper, the portfolio optimization problem is approached. It is a NP-hard problem that consists in periodically creating an instance of the problem, using the time series of the shares value of a stock exchange. The instance is solved to determine the shares set that maximize the return, minimize the risk and minimize the number of selected shares. As far as we know, only three algorithms of

Publications on fuzzy set theory and its applications have grown exponentially. The increasing rate of developments in the field is a response to diverse factors, including the need for robust mathematical approaches that model human-like perceptions, values and decision-making processes in complex and dynamic systems. This study presents a citation analysis of 22 narrowly targeted fuzzy set theory

This paper studies fuzzy adaptive dynamic surface control strategy for nonlinear system with sampled data and time-varying input delay. By utilizing the approximated property of fuzzy logic systems (FLSs), a fuzzy estimator (FE) model is designed to identify the states of the original system, which is mainly used to provide information of estimation states to replace the sampled data of the nonlinear

This paper presents a novel robust fault reconfiguration scheme based on optimized Takagi–Sugeno (T–S) fuzzy model and nonsingular terminal sliding mode observer (NTSMO) with adaptive law for micro-gas turbine (MGS). An optimized T–S fuzzy model is introduced because it can approximate any nonlinear model with arbitrary precision, and an improved imperial competition algorithm (ICA) using adaptive

In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road–rail intermodal transportation system is investigated. According to fuzzy set theory, uncertain demands and capacities are formulated as trapezoidal fuzzy numbers. Soft delivery time windows under a fuzzy environment is established, in which fuzzy periods caused by early

Under unforeseen circumstances, a hierarchical path planning (HPP) scheme combining global and local tasks of an unmanned surface vehicle (USV) is proposed by devising fuzzy artificial potential field (FAPF). Within the HPP scheme, the elite reservation, diversity increment, adaptive mutation probability and adaptive genetic algorithm are incorporated to generate optimally sparse waypoints together

In light of the remarkable diversity of data, arises an interesting and challenging problem of their description and concise interpretation. In a nutshell, in the proposed description pursued in this study, we consider a framework of information granules. The study develops a general scheme composed of two functional phases: (i) clustering data and features forming segments of original data and delivering

The exploratory factor analysis (EFA) method is regarded as one of the most well-known statistical multivariate analysis methods, which is used to discover the underlying structure of a relatively large set of variables. The EFA has a wide range of applications due to its properties such as data reduction. In this paper, the fuzzy EFA (FEFA) method was developed to maintain the uncertain nature of

This paper focuses on the non-weighted asynchronous \(H_{\infty }\) filtering problem for a class of continuous-time switched nonlinear systems. The nonlinearities of subsystems are described by Takagi–Sugeno (T-S) fuzzy models. Using the information of switching instants, the filters are designed to be time-scheduled and separately in the asynchronous and synchronous time intervals. Based on a new

How to effectively deal with uncertain information has traditionally been a concern. The D numbers theory overcomes the limitations of Dempster–Shafer theory and further strengthens the ability of uncertainty modeling. Recently, Yager et al. proposed a soft likelihood function which can effectively combine probability information. Related research has enriched and expanded its connotation, but there

In data processing, measurement of uncertainty is one of the significant evaluation tools, which can describe the uncertainty essence of data. So far, there are few measurable tools to study the uncertainty of type-2 fuzzy information systems (TFISs-2) (the expanded models of fuzzy information systems). This paper is devoted to looking for effective indicators to describe the uncertainty of TFISs-2

Selecting right renewable energy resources (RESs) is emerging as a solution to alleviate energy crisis and environmental pollution. To better address the RESs selection problems, this paper proposes an enhanced Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS). Specifically, the decision information is characterized by linguistic terms and then encoded by interval type-2 fuzzy

The finite-time adaptive fuzzy tracking control problem for a class of strict-feedback uncertain switched systems is investigated in this paper. Based on fuzzy approximation and adaptive dynamic surface control (DSC) technique, a finite-time adaptive state feedback fuzzy controller is developed via the common Lyapunov functions. Different from the existing works on uncertain switched systems, the DSC

When the initial parameters of the fuzzy cerebellar model neural network (FCMNN) are not properly selected, there is a great possibility that the error function converges to the local minimum region or diverges under the gradient descent back propagation (BP) algorithm, which will affect the classification ability of FCMNN. Aiming at this problem, GA is used to optimize the initial center positions

Hesitant fuzzy linguistic term sets (HFLTSs) are applied to deal with situations in which people are hesitant in providing linguistic evaluations and have been widely used in qualitative group decision making processes. Considering the fact that the correlation coefficient has been widely used in many research domains, in this paper, we first present a novel correlation coefficient for HFLTSs. The

The fuzzy time series has received extensive attention since it was proposed and it has been widely used in various practical applications. This study proposes a new fuzzy time series forecasting model which considers a hybrid wolf pack algorithm (HWPA) and an ordered weighted averaging (OWA) aggregation operator for fuzzy time series. The HWPA is adopted to obtain a suitable partition of the universe

In this paper, aiming at the under-actuated problem of the overhead crane systems, a fuzzy logic anti-swing controller is first designed according to operator experience. Moreover, for better configuring the parameters of the controller, an adaptive differential evolution with disturbance factor algorithm (ADE-D) is proposed by introducing the adaptive scaling factor, the dynamic crossover probability

In this study, we concentrate on multiple attribute decision-making (MADM) problems in the probabilistic linguistic preference information surroundings based on novel aggregation operators. Considering interrelationships among the multi-input arguments of probabilistic linguistic term sets (PLTSs), we extend dual Muirhead mean (DMM) operators to the probabilistic linguistic preference environment and

Dual hesitant fuzzy sets (DHFSs) are powerful and efficient to express hesitant preferred and non-preferred information simultaneously. This paper focuses on similarity measures for DHFSs. To do this, it first analyzes the limitations of previous similarity measures for DHFSs. Then, several new dual hesitant fuzzy similarity measures are defined that can avoid the issues of previous ones. To discriminate

In this paper we propose a new decision analysis method combining quantitative logic and fuzzy soft set theory. Firstly, we transform a fuzzy information system into a fuzzy soft set, and then establish a formal language based on the fuzzy soft set, in which the parameters of fuzzy soft set are regarded as atomic formulas, some atomic formulas are connected by the logical connectives and then a logical

Comparing probabilistic linguistic term sets (PLTSs) is quite essential in solving PLTS-expressed multi-attribute group decision-making problems (PLTS-MAGDM). Researchers have designed various comparison measures to obtain the rank of PLTSs. However, most of the existing PLTS comparison measures need additional tedious adjustments before conducting a specific computation. Besides, these measures do

This research is mainly focused on the accurate estimation of the confinement effect for the concrete-filled steel tubular (CFST) that makes it possible to evaluate the interaction between various parameters that affect the confinement effect. To do that, the CFST is analyzed with concrete and steel properties using ANFIS method. With respect to the shape of the CFST, both the circular and rectangle

To achieve better trajectory tracking of the autonomous ground vehicle (AGV), a dual-motor autonomous steering structure and control method are proposed. The model predictive control (MPC) algorithm is utilized to calculate the optimal front wheel angle in real time based on the vehicle information, and dual-motor steering system follows the target angle to achieve trajectory tracking. In this process

This paper presents a novel design for the kinematic control structure of the wheeled mobile robot (WMR) path planning and path-following. The proposed system is focused on the implementation of practical real-time model-free algorithms based on visual servoing. The mainframe of this study is to implement a novel kinematic control structure based on visual sevoing and hybrid algorithms in real-time

In this paper, an improved Type2-NPCM clustering algorithm based on improved adaptive particle swarm optimization called Type2-NPCM-IAPSO is proposed. First, a new clustering algorithm called Type2-NPCM is proposed. The Type2-NPCM algorithm can solve the problems encountered by the algorithms FCM, G-K, PCM and NPCM (sensitivity to noise or aberrant points and local minimal sensitivity), etc. Second

This paper studies the adaptive tracking control problem for a class of nonstrict feedback nonlinear systems with quantized inputs and actuator faults. Compared with existing works on quantized control problem, the asymmetric hysteresis quantizer is considered in the actuator failure problem in this paper. To resolve the control challenge caused by the quantization effect, a nonlinear decomposition

Interval rough numbers play an important role in dealing with complex fuzzy relationships. In this paper, a group decision-making (GDM) model based on interval rough multiplicative reciprocal (IRMR) matrix is proposed. Firstly, the inconsistency, satisfactory consistency and complete consistency of the IRMR matrix are defined from the perspective of set theory. Secondly, an improved method for the

A variable-fuzzy-predictor-based predictive control approach is presented to solve the dynamic trajectory tracking problem of an autonomous underwater vehicle (AUV) in a three-dimensional underwater environment. To adapt to the characteristics of AUV’s motion such as nonlinearity and time-varying dynamics, a predictive controller framework is proposed based on a variable fuzzy predictor whose structure

This paper proposes a novel cooperative control method based on cyclic pursuit algorithm and fuzzy control idea, to accomplish reconfiguration of multi-agent formation in 3D space. The idea is to use nonlinear cyclic pursuit control within the formation’s longitudinal motion plane, and use fuzzy control-based piecewise proportional derivative (PD) controller for cooperative control in the normal direction

In this paper, the design problem of intelligent ship autopilot with unmeasured yaw rate and input saturation is investigated based on adaptive fuzzy control. First, an adaptive fuzzy output feedback controller is proposed, then, to improve the convergence speed of the tracking error in the sense of finite time, a finite-time adaptive fuzzy output feedback controller is also designed to improve the

In this paper, a Pythagorean fuzzy decision-making method based on overall entropy is presented. First, a new definition is proposed for fuzzy entropy for any given Pythagorean fuzzy set (PFS). The proposed definition is based on the relationship between the fuzziness contained in the given PFS and the distance from a point to a line on a projection plane. Some related properties are introduced. Second

This paper develops an adaptive robust control scheme combined with optimal design for the unmanned helicopter tail reduction (UHTR) system. The dynamical model of the UHTR system with uncertainties is established. The uncertainties are assumed to be bounded and expressed by fuzzy set theory. With this prerequisite, an adaptive robust controller is proposed to drive the system to meet the trajectory

In this paper, the issues about weighted \(H_\infty\) performance analysis and \(H_\infty\) control for the stochastic switched nonlinear systems (SSNSs) with multiplicative noise are investigated. The mode-dependent average dwell time (MDADT) method is used to deal with the switching in different modes. Firstly, we get a sufficient condition to show that the considered system with all stable subsystems

The present paper proposes a number of models for calculating the average efficiency of two-stage networks using DEA and DEA-R with fuzzy data. If the input, intermediate, and output parameters are available in a two-stage network, DEA and DEA-R models can be used to compute the efficiency. When evaluating decision-making units (DMUs) in two-stage network DEA, the respective programming models are

This paper has proposed a classification rule base mining algorithm combining the genetic algorithm and intuitionistic fuzzy-rough set for large-scale intuitionistic fuzzy information system. The algorithm has proposed innovatively the definitions and measurement metrics of completeness, interaction and compatibility describing the whole rule base, and constructed a multi-objective optimization model

Mitotic counts are widely used as a metric for cellular proliferation for prognosis and to determine the aggressiveness of individual cancers. This study presents a less labor-intensive method to count mitotic cells in breast cell sections. The proposed algorithm involves two phases: candidate segmentation and detection. During candidate segmentation, images are filtered through a blue ratio threshold