A note on “Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets”

In a recent paper in this journal, Ashtiani et al. [1] proposed a fuzzy TOPSIS method based on interval-valued fuzzy sets. They changed the information of example that expressed by Chen [2] for the purpose of adjustment with their method and applied their method for solving the changed example. When we investigated their method, we found that Although, Ashtiani et al.’s method is really interesting, but applying it for some fuzzy MCDM problems leads to the incorrect solution and results. In other words, Ashtiani et al.’s method is not applicable to some fuzzy MCDM problems. In this paper we try to eliminate this problem.     

Research on vacuum gripper based on fuzzy control for micromanipulators

This paper presents a vacuum gripper （as an actuator of an intelligent micromanipulator） for micro objects （with a diameter of 100 - 300μm） assembly tasks. The gripper is composed of a vacuum unit and a control unit. The vacuum unit with a proportional valve and a pressure sensor, and the control unit with a PC ＋ MCU two-layered control architecture are designed. The mechanical structure, workflow and major programs of the micro-gripper are presented. This paper discusses the major components of the adhesion force acting on micro objects. Some equations of the operation conditions m three phases of pick, hold and place are derived by mechanics analysis. The pneumatic system＇s pressure loss is inevitable. There are some formulas for calculating the amount of the pressure loss, but parameters in formulas are diffficult to be quantified and evaluated. To control the working pressure accurately, a pressure controller based on fuzzy logic is designed. With MATLAB＇s fuzzy logic toolbox, simulation experiments are performed to validate the performance of the fuzzy PD controller. The gripper is characterized by a steady and reliable performance and a simple structure, and it is suitable for handling micro objects with a sub-millimeter size.     

Collaborative modelling or participatory modelling? A framework for water resources management

Decision Support Systems, and, more recently, participatory and collaborative modelling have emerged as a response to increased focus on stakeholder participation in modelling activities for certain fields like water resources management. Researchers and practitioners frequently use ‘buzzwords’ such as ‘participatory modelling’ and ‘collaborative modelling’. In some cases, both terms are used interchangeably, largely due to unclear distinction between them in literature. This article draws the line between participatory and collaborative modelling by using levels of participation and cooperation as conditioning dimensions. Based on this methodology, a new generic framework is presented. This framework can help identify determinant features of both modelling approaches currently used in water resources management. It permits analysis of these approaches in terms of context, specific use, information handling, stakeholder involvement, modelling team and means. The article concludes with an application of the framework to a collaborative modelling approach carried out for a groundwater study in the Netherlands.     

A new arc detection method based on fuzzy logic using S-transform for pantograph–catenary systems

pantograph–catenary system is one of the critical components used in electrical trains. It ensures the transmission of the electrical energy to the train taken from the substation that is required for electrical trains. The condition monitoring and early diagnosis for pantograph–catenary systems are very important in terms of rail transport disruption. In this study, a new method is proposed for arc detection in the pantograph–catenary system based signal processing and S-transform. Arc detection and condition monitoring were achieved by using current signals received from a real pantograph–catenary system. Firstly, model based current data for pantograph–catenary system is obtained from Mayr arc model. The method with S-transform is developed by using this current data. Noises on the current signal are eliminated by applying a low pass filter to the current signal. The peak values of the noiseless signals are determined by taking absolute values of these signals in a certain frequency range. After the data of the peak points has been normalized, a new signal will be obtained by combining these points via a linear interpolation method. The frequency-time analysis was realized by applying S-transform on the signal obtained from peak values. Feature extraction that obtained by S-matrix was used in the fuzzy system. The current signal is detected the contdition as healthy or faulty by using the outputs of the fuzzy system. Furthermore the real-time processing of the proposed method is examined by applying to the current signal received from a locomotive.     

H∞ Adaptive tracking control for switched systems based on an average dwell-time method

This paper investigates the H_∞ state tracking model reference adaptive control (MRAC) problem for a class of switched systems using an average dwell-time method. First, a stability criterion is established for a switched reference model. Then, an adaptive controller is designed and the state tracking control problem is converted into the stability analysis. The global practical stability of the error switched system can be guaranteed under a class of switching signals characterised by an average dwell time. Consequently, sufficient conditions for the solvability of the H_∞ state tracking MRAC problem are derived. An example of highly manoeuvrable aircraft technology vehicle is given to demonstrate the feasibility and effectiveness of the proposed design method.     

Commentary on “Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach”

Chou et al. (Applied Soft Computing 12 (2012) 64–71) used combination of fuzzy AHP (Analytic Hierarchy Process) and fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) in human resource for science and technology (HRST). For applying the fuzzy DEMATEL method there is a need to find the multiplicative inverse of a fuzzy matrix. In this paper, it is pointed out that the method, used by Chou et al. for evaluating the multiplicative inverse of a fuzzy matrix, is not valid. Hence, the method, proposed by Chou et al., is not valid. Furthermore, it is pointed out that this flaw can be resolved by using the existing method (International Journal of Computer Mathematics, 86 (8), (2009) 1433–1452) to find the multiplicative inverse of a fuzzy matrix.     

Development of dense models of the Earth’s surface based on the semiglobal matching method for the case of multiple overlapping images

A method is developed for constructing a three-dimensional digital surface model based on the use of aerial images with multiple overlapping. The specific feature of this study is the use of the multiview matching method instead of stereo matching. The method is based on adapting the energy aggregation algorithm, which was proposed in the semiglobal matching (SGM) method, to the object space, as well as using the one-to-many scheme of cost calculation. The reconstructed scene is represented as a voxel grid. A high-performance implementation of the digital surface model construction at all stages is proposed based on the massive parallelization of computations on a graphics processing unit.     

A novel group decision model based on mean–variance–skewness concepts and interval-valued fuzzy sets for a selection problem of the sustainable warehouse location under uncertainty

Recently, sustainable warehouse location has been regarded as one of the most critical and significant decision problems for long-term planning in the supply chain. This strategic decision can be effected by different quantitative and qualitative evaluation criteria via three dimensions of the sustainability. Main theme of the paper is to select the most optimal location decision from a number of potential sustainable warehouse candidates. For this purpose, this paper presents a novel multi-criteria decision-making model by a group of supply chain experts or decision makers with interval-valued fuzzy setting and asymmetric uncertainty information. Concepts of mean, variance and skewness are introduced into the proposed group decision model, and their mathematical relations are defined based on a fuzzy possibilistic statistical approach. Then, new relations in this model are presented for obtaining ideal solutions under uncertainty with two high and low values of the possibilistic mean and possibilistic standard deviation, along with the possibilistic cube root of skewness. In addition, novel separation measures and new fuzzy ranking index of hybridized relative closeness coefficients are presented to provide final preference order of warehouse location candidates under uncertain conditions. Finally, a sustainable warehouse location selection problem in a pharmaceutical company is presented and solved by the proposed group decision model to demonstrate its applicability and suitability.

     

Robust adaptive fuzzy tracking control for a class of strict-feedback nonlinear systems based on backstepping technique

In this paper, the robust adaptive fuzzy tracking control problem is discussed for a class of perturbed strict-feedback nonlinear systems. The fuzzy logic systems in Mamdani type are used to approximate unknown nonlinear functions. A design scheme of the robust adaptive fuzzy controller is proposed by use of the backstepping technique. The proposed controller guarantees semi-global uniform ultimate boundedness of all the signals in the derived closed-loop system and achieves the good tracking performance. The possible controller singularity problem which may occur in some existing adaptive control schemes with feedback linearization techniques can be avoided. In addition, the number of the on-line adaptive parameters is not more than the order of the designed system. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed control scheme.     

HAT： an efficient buffer management method for flash-based hybrid storage systems

Flash solid-state drives （SSDs） provide much faster access to data compared with traditional hard disk drives （HDDs）. The current price and performance of SSD suggest it can be adopted as a data buffer between main memory and HDD, and buffer management policy in such hybrid systems has attracted more and more interest from research community recently. In this paper, we propose a novel approach to manage the buffer in flash-based hybrid storage systems, named hotness aware hit （HAT）. HAT exploits a page reference queue to record the access history as well as the status of accessed pages, i.e., hot, warm, and cold. Additionally, the page reference queue is further split into hot and warm regions which correspond to the memory and flash in general. The HAT approach updates the page status and deals with the page migration in the memory hierarchy according to the current page status and hit position in the page reference queue. Compared with the existing hybrid storage approaches, the proposed HAT can manage the memory and flash cache layers more effectively. Our empirical evaluation on benchmark traces demonstrates the superiority of the proposed strategy against the state-of-the-art competitors.     

Sensor‐independent analysis method for hyperspectral data based on the pattern decomposition method

This paper describes a modified pattern decomposition method with a supplementary pattern. The proposed approach can be regarded either as a type of spectral mixing analysis or as a kind of multivariate analysis; the later explanation is more suitable considering the presence of the additional supplementary patterns. The sensor‐independent method developed herein uses the same normalized spectral patterns for any sensor: fixed multi‐band (1260 bands) spectra serve as the universal standard spectral patterns. The resulting pattern decomposition coefficients showed sensor independence. That is, regardless of sensor, the three coefficients had nearly the same values for the same samples. The estimation errors for pattern decomposition coefficients depended on the sensor used. The estimation errors for Landsat/MSS and ALOS/AVNIR‐2 were larger than those of Landsat/TM (ETM+), Terra/MODIS and ADEOS‐II/GLI. The latter three sensors had negligibly small errors.     

Impacts of urban development on urban water management – Limits of predictability

This study evaluates how random variations in urban development affect projections of urban water management over long time horizons, based on combined simulations of urban development and water management. The urban development was simulated based on existing procedural tools; however, novel procedures were implemented to allow the simulation of re-development in existing areas. The urban layout was parameterised based on the characteristics of existing building stock. A state-of-the-art hydraulic simulation tool was applied to simulate urban water systems. Experiments were conducted based on different degrees of random variation in the projections of urban development. These ranged from simply shuffling the sequences of urban developments foreseen in planning documents, to simulating urban growth with fixed growth rates but without zoning regulations, to simulations where both the growth rates and urban development locations were selected based on past development characteristics. Odense (a city in Denmark) was analysed using this paradigm. The impacts on the annual flow volumes, combined sewer overflows, exceedances of hydraulic pipe capacity, and surcharge volumes were evaluated. In general, the projections of the urban water management parameters were strongly affected by the random variations in the locations of urban development. In addition, most trends resulting from changing population growth rates could only be identified on spatial scales above 10 km². Projections on longer time horizons were less affected by the random variations in urban development locations, as bounded simulation areas were considered. In conclusion, conceptual models are considered sufficient for performing combined simulations of urban development and urban water management in exploratory assessments.     

Research on fast implementation of Elliptic Curve Cryptosystem based on object-oriented method

With the fast development of cryptography research and computer technology, the cryptosystems of RSA and Diffe-Hellman are getting more and more unsafe, and Elliptic Curve Cryptosystem is becoming the trend of public cryptography in the future. Object-oriented technology is mainly used as tools, and Elliptic Curve Cryptosystem is divided into several layers, every of which corresponds a class. The properties and methods of these classes are discussed, and some methods are implemented. In the end, the advantages are analyzed, and the cryptosystem implemented with advanced programming language is easy to transplant.     

PI control based on fuzzy set-point weighting tracking for hydraulic crane boom system

A PI control strategy based on fuzzy set-point weighting following was proposed for the active damping control of a hydraulic crane boom system （HCBS）. Two valve-controlled PI controllers, which include a proportional feedforward controller based on fuzzy set-point weighting following and a limited semi-integrator（LSI）, are designed respectively. LSI is used to limit output signal and to prevent wind up at the low frequency of the spectrum. By using a range camera and an electronic feedback control, the tip damping on the HCBS can be adjusted artificially. A collaborative control simulation technique of HOPSAN and MATLAB/SIMULINK is applied to the controller design. Simulation results show that the proposed PI control system has less overshoot as well as faster response. The tip damping on the HCBS during operation is improved.     

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.     

Output regulation of nonlinear singularly perturbed systems based on T-S fuzzy model

1IntroductionNonlinear singularly perturbed systems arise in a widevariety of engineering applications,representative examplesinclude catalytic continuous stirred_tank reactors[1],biochemical reactors[2],fluidized catalytic crackers[3],flexible mechanical systems[4],electromechanical networks[5],etc.For such systems,the output regulation problem,i.e.the problem of having the output tracking reference(or rejecting disturbance)signals produced by someexternal generator,is ofimportance.In linear …     

Dynamic modeling of SOFC based on a T–S fuzzy model

The operating temperature and voltage are the key parameters affecting the performance of Solid Oxide Fuel Cell (SOFC). In this article a Takagi–Sugeno (T–S) fuzzy model is proposed to describe the nonlinear temperature and voltage dynamic properties of the SOFC system. During the process of modeling, a Fuzzy Clustering Means (FCM) method is used to determine the nonlinear antecedent parameters, and the linear consequent parameters are identified by a recursive least squares algorithm. The validity and accuracy of modeling are tested by simulations. The simulation results show that it is feasible to establish the dynamic model of SOFC by using the T–S fuzzy identification method.     

H∞ control of nonlinear continuous-time systems based on dynamical fuzzy models

This paper presents a solution of the H_∞ control problem for a class of continuous-time nonlinear systems. The method is based on a fuzzy dynamical model of the nonlinear system. A suitable piecewise differentiate quadratic (PDQ) Lyapunov function is used to establish asymptotic stability of the closed-loop system. Furthermore, a constructive algorithm is developed to obtain the stabilizing feedback control law. The controller design algorithm involves solving a set of suitable algebraic Riccati equations. An example is given to illustrate the application of the method     

Development of optimal water supply plan using integrated fuzzy Delphi and fuzzy ELECTRE III methods—Case study of the Gamasiab basin

This paper presents a novel method for the development of an optimal water supply plan showcased using data from the Gamasiab basin, located in Kermanshah province, Iran, concerning new dams that are being constructed in this semi-arid region. In this paper, a new group multi-criteria decision-making (MCDM) plan is proposed by combining two MCDM methods based on the fuzzy Delphi and fuzzy ELECTRE III methods that convert the experts' opinions to triangular fuzzy numbers based on the level of uncertainty associated with various quantitative and qualitative criteria. Considering the opinions of four non-stakeholder experts and data analysis using the fuzzy Delphi method, the criteria were evaluated. Then, by analysing the results using the fuzzy ELECTRE III method, the final ranking of scenarios is obtained. A sensitivity analysis was conducted to assess the effect of uncertainty on the performance of the decision-making system in scenarios ranking. The total expense, flood control, reservoir capacity and diversion and water transfer played a significant role in selecting the optimal scenario. Additionally, a hydrologic model was developed to evaluate the performance of the optimal scenario in terms of qualitative criteria. The data indicated that there was a good agreement between the results obtained from the hydrological model and the scenario ranking by the employed method. Altogether, a comparison of the proposed method with other MCDM methods, including fuzzy analytic hierarchy process and fuzzy technique for order preference by simulation of ideal solution, indicated that the results of the employed method matched more closely to the local experts' opinion.     

A solving method based on neural network for a class of multi-leader–follower games

In this paper, we present a new solving approach for a class of multi-leader–follower games. For the problem studied, we firstly propose a neural network model. Then, based on Lyapunov and LaSalle theories, we prove that the trajectory of the neural network model can converge to the equilibrium point, which corresponds to the Nash equilibrium of the problem studied. The numerical results show that the proposed neural network approach is feasible to the problem studied.