A Neuro T-Norm Fuzzy Logic Based System

In this study, we are first examining well-known approach to improve fuzzy reasoning model (FRM) by use of the genetic-based learning mechanism [1]. Later we propose our alternative way to build FRM, which has significant precision advantages and does not require any adjustment/learning. We put together neuro-fuzzy system (NFS) to connect the set of exemplar input feature vectors (FV) with associated output label (target), both represented by their membership functions (MF). Next unknown FV would be classified by getting upper value of current output MF. After that the fuzzy truths for all MF upper values are maximized and the label of the winner is considered as the class of the input FV. We use the knowledge in the exemplar-label pairs directly with no training. It sets up automatically and then classifies all input FV from the same population as the exemplar FVs. We show that our approach statistically is almost twice as accurate, as well-known genetic-based learning mechanism FRM.

Switching Logic-based Adaptive Robust Control of Nonlinearly Parameterized Uncertain Systems

在这份报纸，切换基于逻辑的适应柔韧的控制为一个类被建议非线性地 parameterized 系统(NFS ) 。明确地，控制器主要由一项柔韧的类型条款组成探讨系统无常，和切换逻辑调节机制更新深奥控制获得。构造控制器完成全球一致地最终的固定(GUUB ) 系统错误的结果，和模拟结果被包括表明控制法律的有效性。

Three-dimensional fuzzy logic system for process modeling and control

The traditional fuzzy logic system （FLS） can only model and control the process in two-dimensional nature. Many of real-world systems are of multidimensional features, such as, thermal and fluid processes with spatiotemporal dynamics, biological systems, or decision-making processes that contain stochastic and imprecise uncertainties. These types of systems are difficult for the traditional FLS to model and control because they require a third dimension for spatial or probabilistic information. The type-2 fuzzy set provides the possibility to develop a three-dimensional fuzzy logic system for modeling and controlling these processes in three-dimensional nature.

Nonlinear inverse modeling of sensor based on back-propagation fuzzy logical system

Objective To correct the nonlinear error of sensor output,a new approach to sensor inverse modeling based on Back-Propagation Fuzzy Logical System(BP FS) is presented.Methods The BP FS is a computationally efficient nonlinear universal approximator,which is capable of implementing complex nonlinear mapping from its input pattern space to the output with fast convergence speed.Results The neuro-fuzzy hybrid system,i.e.BP FS,is then applied to construct nonlinear inverse model of pressure sensor.The experimental results show that the proposed inverse modeling method automatically compensates the associated nonlinear error in pressure estimation,and thus the performance of pressure sensor is significantly improved.Conclusion The proposed method can be widely used in nonlinearity correction of various kinds of sensors to compensate the effects of nonlinearity and temperature on sensor output.

An Application Expert System for Evaluating Effective Factors on Trust in B2C WebsitesTrust, Security, ANFIS, Fuzzy Logic, Rule Based Systems, Electronic Commerce

In new environments of trading, customer's trust is vital for the extended progress and development of electronic commerce. This paper proposes that in addition to known factors of electronic commerce B2C websites such a design of websites, security of websites and familiarity of website influence customers trust in online transactions. This paper presents an application of expert system on trust in electronic commerce. Based on experts’ judgment, a frame of work was proposed. The proposed model applies ANFIS and Mamdani inference fuzzy system to get the desired results and then results of two methods were compared. Two questionnaires were used in this study. The first questionnaire was developed for e-commerce experts, and the second one was designed for the customers of electronic websites. Based on AHP method, Expert Choice software was used to determine the priority of factors in the first questionnaire, and MATLAB and Excel were used for developing the fuzzy rules. Finally, the fuzzy logical kit was used to analyze the generated factors in the model. Our study findings show that trust in EC transactions is strongly mediated by perceived security.

Institutional Change Logic of the Reform of the Emergency Management of the Super - ministry System

As the typical institutional change,the reform of the emergency management of the super-ministry system embodies itself not only in the integration of emergency function and the combination of organizations,but also in the mechanism reform of the emergency management.As a result,it cannot avoid the accumulation logic,the intentional logic and the isomorphic logic of institutional change.It manifests as follows:from the perspective of the accumulation logic,the reform of the emergency management of the super-ministry system is influenced by the historical context and the original institution;from the perspective of intentional logic,it is influenced by the thinking set and the benefit game;from the perspective of isomorphic logic,it is constrained by the political and social structure and the institutional supply shortage.

Fuzzy Logic Based Evolving System and One Kind of Competition Mechanism

In this paper, an evolving system is introduced. That any system is evolving means that any entity in the system is in developing state and entities compete with each other. Any entity can be represented by development of the entity and its environment consisting of a closed cycle. Any subsystem is assigned by a management. The competing controller controls competing entities and arranges them in any advantage order by its common rules and local rules of any subsystem. Each entity can use its competing rules to change the evaluation by any subsystem containing it. This kind of changes leads the entity into its increase of the position in an advantage order.

A Diagnostic Method Based on Path Information for Logical Divisible System

The classification of system based on faults is studied. Knowledge representation and reasoning technology are comprehensively discussed for logical divisible system, and then a method, named path information extremum diagnosis method(PIEDM), is proposed.PIEDM considers all nodes' information at one step, and so, has a high efficiency.

Optimization in Site Selection of Wind Turbine for Energy Using Fuzzy Logic System and GIS—A Case Study for Gujarat

The development of new wind energy project requires studying of many parameters to achieve maximum benefits at the cost of minimum environmental impacts. Using Geographic Information System (GIS), an analytical framework has been developed in this paper with fuzzy logic to evaluate the suitable site for turbines for optimum energy output. The criteria for suitable site for energy optimization are environmental, physical and human factors. The present study helps to assess the appropriate sites for the wind turbines in Gujarat. The result obtained from the study conveys the suitability of the development of wind turbines along the western parts of Gujarat. The suggested model could be used for the future site selection of the wind turbine which in turn could be of orientation for energy planners and decision makers.

Application of the Constrained Predicated Nets and Interval Logic to Production Systems

A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a Petri net with predicated transition. All components of the net are expressed by annotation which is defined on rational set Q. The analysis method for the plant is interval temporal logic represented by Petri nets. This paper combines the above two methods to synthesize the hybrid system, gives a simple and clear expression of the expected action of the studied plant.

PID and Fuzzy Logic Control of Ball and Beam System Using Particle Swarm Optimization

In this research, we carried out the modeling of the ball and beam system (BBS) within the MATLAB/Simulink framework by applying both proportional-integral-derivative (PID) and fuzzy logic control strategies to govern the dynamics of this constructed model. The underlying non-linear dynamic equations adjusting the behavior of the BBS system are based on Newton’s second law of motion. The physical installation of the BBS, designed for potential real-time application, comprises a lengthy beam subject to movement through the action of a DC servomotor, with a ball traversing the beam in a reciprocating manner. A distance sensor is strategically placed in front of the beam to determine the exact position of the ball. In this system, an electrical control signal applied to the DC servomotor causes the beam to pivot about its horizontal axis, thereby enabling the ball to move freely along the beam's length. To avoid the risk of losing the ball equilibrium on the beam and to achieve precise system control, a mathematical model was devised and implemented within the MATLAB/Simulink environment. The use of the particle swarm optimization (PSO) algorithm was aimed at tackling the task of refining and optimizing the PID controller specifically designed for the linearized ball and beam control system. The presented system is controlled using both PID and fuzzy logic, and the use of the PSO algorithm enhances the system’s responsiveness efficiency.

Strong Completeness of Medium Logic System

The strong completeness of medium logic system is discussed. The following results are proved： medium propositional logic system MP and its extension MP^＊ are strong complete; medium predicate logic system MF and its extensions （MF^＊ and ME^＊ ） are not strong complete; and generally, ff a consistent formal system is not strong complete, then any consistent extensions of this forreal system are not strong complete either.

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

The target of this paper is to model a Maximum Power Point Tracker (MPPT) using a Fuzzy Logic Control (FLC) algorithm and to investigate its behavior with a battery load. The advantage of this study over other studies in this field is that it considers a battery load rather than the commonly used resistive load especially when we deal with the relationship between MPPT and system load. The system is about 60 kW which is simulated under various environmental conditions by Matlab/Simulink program. For this type of non-linear application, FLC naturally offers a superior controller for the real load case. The artificial intelligence approach also benefits from this method for overcoming the complexity of nonlinear system modelling. The results show that FLC provides high performance for MPPT of PV system with battery load due to its low settling time and limited oscillation around the steady state value. These are assistant factors for increasing battery life.

Dehydration of Agro Products in a Hybrid Solar Dryer Controlled through a Fuzzy Logic System

Drying is one of the most energy-intensive processes in agro-products industry. For this reason, using solar energy appears as an attractive not polluting alternative to be used in drying processes. However, the daily and seasonal fluctuations in the radiation level require using energy accumulators with phase change materials (paraffin wax), to have a continuous drying processes. In hybrid solar dryers with energy accumulation system, a control system is essential to coordinate the control valves that allow the income of air that comes from the solar panel or from the energy accumulator. In this work, we implemented an advances multivariable control system that uses fuzzy logic in the hybrid solar dryer. The dryer includes an energy accumulator panel with paraffin wax as phase change material. The input variables were ambient temperature and solar radiation, both not controllable. The controlled variables were the opening level of the solar panel and accumulator energy valves. The control program consisted in an algorithm implemented with the “Fuzzy” toolbox in Matlab. Data were acquired with OPTO 22. The control system performed adequately when used to dehydrate mushroom slices and plums. Closing or opening the respective valves as a response to the variations of solar radiation and ambient air temperature allowed optimizing the use of solar energy.

Analyses and Simulation of Fuzzy Logic Control for Suspension System of a Track Vehicle

The vibration caused by terrible road excitation affects the ride quality and safety of track vehicles. The vibration control of suspension systems is a very important factor for modern track vehicles. A fuzzy logic control for suspension system of a track vehicle is presented. A mechanical model and a system of difft, rential equations of motion taking account of the mass of loading wheel are established. Then the fuzzy logic control is applied to control the vibration of suspension system of track vehicles for sine signal and random road surfaces. Numerical simulation shows that the maximum acceleration of suspension system can be reduced to 44 % of the original value for sine signal road surface, and the mean square root of acceleration of suspension system can be reduced to 21% for random road surface. Therefore, the proposed fuzzy logic control is an efficient method for the suspension systems of track vehicles.

Microgrid Design Including Fuzzy Logic Controlled Storage System

Smart grid design and structures are somehow depending on the way of designing and operating Microgrids. In this research a unique design of microgrid is proposed as in medium tension isolated power distribution system contains diesel generation unit and photovoltaic generation. Storage system is a part of the control strategy to reduce the diesel usage and to maintain the balance between generation and demand which might be disturbed due to the presence of PV system. Fuzzy logic control scheme has been chosen compared with conventional controller to be the main controller for both the diesel unit and storage system. Promising result has been found by digital simulation using Matlab Simulink proving the possibility of reducing the dependency on fossil fueled generators and increase the utilization of renewable energy.

Timed automata for metric interval temporal logic formulae in prototype verification system

Based on analysis of the syntax structure and semantics model of the metric interval temporal logic （MITL） formulas, it is shown how to transform a formula written in the real-time temporal logic MITL formula into a fair timed automaton （TA） that recognizes its satisfying models with prototype verification system （PVS） in this paper. Both the tabular construction＇s principles and the PVS implementation details are given for the different type of MITL formula according to the corresponding semantics interpretations. After this transformation procedure, specifications expressed with MITL formula can be verified formally in the timed automata framework developed previously.

Robust Control of Brushless Servo System Based on the Principle of Fuzzy Logic

An application of fuzzy logic in brushess servo system is presented. FLC(fuzzy logic control)provides a control strategy regarding to uncertain model, so it has certain robustness. The proposed method improves the robust performance of the system, so as to suppress rapidly the state error caused by both parameter variation and forced disturbance. In order to optimize the characteristic of the FLC, PID and on-line adaptive controls are applied. Experiments show that the proposed method is effective.

Study on Information System Architecture Based on Service-Dominant Logic

As goods-dominant logic lexicon transitions to service-dominant logic, based on the knowledge and structure dimensions of IT and business alignment, combined with the IT flexible, we design information system architecture diagram of y group. We try to solve y group functionality and data misfit domains, aligning information system and business in operational level to response to changes in the environment.