scholarly journals Fuzzy Logic for Intelligent Control System Using Soft Computing Applications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2617
Author(s):  
Catalin Dumitrescu ◽  
Petrica Ciotirnae ◽  
Constantin Vizitiu
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Distributed Intelligence ◽  
High Level ◽  
The Impact ◽  
Fuzzy Subsets

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

scholarly journals Effect of Interventional Programme on Enhancing Empowerment Status through Decision Making Skills of Tribal Working Women in Utnoor Mandal Adilabad District, India

2021 ◽  
pp. 41-45
Author(s):  
N. Sandhya Rani ◽  
M. Sarada Devi
Keyword(s):  
Decision Making ◽  
Working Women ◽  
Total Sample ◽  
Average Level ◽  
Sample Population ◽  
Test Results ◽  
Low Level ◽  
Tribal Women ◽  
High Level ◽  
The Impact

Empowerment of tribal women is one of the central issues in the process of development all over the world. Empowerment is the process that allows one to gain the knowledge and attitude needed to cope with the changing world and the circumstances in which one lives [1]. Women empowerment is a process in which women gain greater share of control over material, human and intellectual resources as well as control over decision-making in their home, community, society and nation. Given the need to analyze the empowerment status of tribal women, the present study aimed to enhance the empowerment status through enhancing decision-making skills of tribal working women in India. The specific objective is to study the impact of intervention on enhancing status of empowerment through decision-making skills of tribal working women in Utnoor Mandal Adilabad district. The total sample population for the study was 50 tribal working women, and data was analyzed using a paired t test. Results revealed that at pretest, majority of the women were at average level of decision-making skills (78%), 12% were at low level and only 10% were at high level. After the intervention, post test results revealed that 74% of the women were high in decision making skills and remaining 26% were at average level. Interestingly, none of the respondents had low level of life skills. Thus, intervention found to be effective among women respondents to develop and enhance their empowerment status through decision-making skills.

The Design of Neuro-Fuzzy Control System Based on Data Fusion

2014 ◽  
Vol 678 ◽  
pp. 406-409
Author(s):  
Xiao Rong Fu
Keyword(s):  
Nonlinear Systems ◽  
Data Fusion ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Control Technique ◽  
Fusion Method ◽  
Neuro Fuzzy ◽  
Simulation Results ◽  
Using Data ◽  
Self Learning

An adaptive neuro-fuzzy controller of nonlinear systems is presented based on data fusion method. It reduces the input dimension of the controller using data fusion technique and simplifies the fuzzy controller’s design. The fuzzy controller was designed with self-learning of neural networks. The simulation results show that the performance of the system is superior to that using conventional fuzzy controller. It is rewarding for the research on combination of data fusion method and intelligent control technique of nonlinear systems.

scholarly journals Consumer Diversity In Multicultural Arenas: An Investigation Of Social Influences Between Asians And Westerners

2011 ◽  
Vol 5 (12) ◽  
Author(s):  
Kritika Kongsompong
Keyword(s):  
Decision Making ◽  
Locus Of Control ◽  
Social Influence ◽  
Cultural Orientation ◽  
Purchasing Decisions ◽  
External Locus ◽  
Cultural Orientations ◽  
High Level ◽  
The Impact ◽  
Consumer Diversity

The impact of peoples orientation with regard to Collectivism/Individualism and to Locus of Control on the extent to which they are subject to social influence has never been investigated cross culturally in the context of consumer behavior in making purchasing decisions. The objective of this research is to compare the cultural orientations of people in the East and West, and to observe the effect of social influence in their decision making. In particular, this paper examines and adds evidence to the mutually exclusive cultures: Singapore, Thailand, Australia, and America. Hofstedes typology of cultures is reconfirmed and empirically associated with specific social influence variables on decision making. The findings provide either whole or partial supports for the hypotheses. In general, high collectivism is positively related with external locus of control and results in high level of social influence. There are exceptions, however, which highlight the need to incorporate other factors into understanding the role that cultural orientation plays in decision making.

SOFT COMPUTING: AN INTRODUCTION

2018 ◽  
Vol 8 (6) ◽  
pp. 63
Author(s):  
Matthew N. O. Sadiku ◽  
Yonghui Wang ◽  
Suxia Cui ◽  
Sarhan M. Musa
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Low Cost ◽  
Computational Techniques ◽  
Inaccurate Information ◽  
Major Benefit ◽  
Partial Truth ◽  
Human Decision

Soft computing (SC) is a newly emerging multidisciplinary field. It is a collection of computational techniques, such as expert systems, fuzzy logic, neural networks, and evolutionary algorithms, which provide information processing capabilities to solve complex practical problems. The major benefit of SC lies in its ability to tolerate imprecision, uncertainty, partial truth, and approximation in processing imprecise and inaccurate information and simulating human decision making at low cost. This paper provides a brief introduction on soft computing.

The Effect of Neighboring Cells on Handover Decision Making Based on Fuzzy in the WCDMA Network

2017 ◽  
Vol 5 (2) ◽  
pp. 52-58
Author(s):  
Akbar Nur
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Base Station ◽  
Test Method ◽  
User Mobility ◽  
Handover Decision ◽  
Final Project ◽  
Soft Handover ◽  
Hard Handover ◽  
The Impact

In channel transfer (handover) from one Base Station to another Base Station. The purpose of this final project is to analyze the effect of neighboring cells on handover decisions on WCDMA networks based on fuzzy, in this handover process, handover decisions use several parameters related to handovers and supported by fuzzy logic. Relatively high user mobility demands a guarantee until the use of the service ends, the impact of user mobility results in the output being analyzed for this handover decision to help give consideration to the optimal handover decision. The method used is Tsukamoto fuzzy logic, for decision making, while the measurement method In the field, the drive test method is carried out by measuring the signal level around the base station area, and comparing the results of the two methods. Comparison of handover decisions between the results of fuzzy logic and measurements, for example for the results of no proper in fuzzy logic, yields a rate value of 0% for soft handovers and 100% for hard handovers, and for proper results in fuzzy logic, yields a rate value for measurement. 95.22% for soft / soft handover and 4.72% for hard handover

A Fuzzy Logic-Based System for Controlling the Temperature of Steam Exiting a Superheater for the Purpose of Preemptive Perturbation Compensation

2021 ◽  
Vol 22 (4) ◽  
pp. 181-190
Author(s):  
M. Yu. Ryabchikov ◽  
E. S. Ryabchikova ◽  
S. A. Filippov
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Negative Feedback ◽  
Degrees Of Freedom ◽  
Fuzzy Controller ◽  
Linear Structure ◽  
Transition Process ◽  
Smith Predictor ◽  
Steam Temperature ◽  
The Impact

This paper discusses the issue of adjusting the temperature of steam exiting a superheater in an environment that is affected by perturbations due to the sudden and significant fluctuations in the inlet steam temperature. Using the superheater at the Magnitogorsk Iron & Steel Works as an example, we highlight that a slow response to the aforementioned perturbations in the systems that adjust for deviations leads to undesired rises and drops in the outlet steam temperature. We review the current suggestions on adjusting the temperature of steam exiting a superheater and determine the main reasons behind the drop in adjustment quality. These reasons are related to a significant lag and the variability of the control object’s features, which make preemptive perturbation control difficult. In order to control such environments, we propose a system with two degrees of freedom, which combines a proportional-integral controller and a fuzzy logic-based controller. In the system that we are proposing, the changes in the controlled parameter (depending on the input value) are adjusted within the main loop that has a standard controller and negative feedback, while the perturbations are removed by using a secondary loop, which also has negative feedback, a fuzzy logic-based controller, and a simulation of the object without the component that accounts for the lag. For situations when the information on the object’s features is precise, we describe the specifics of the loops’ interaction, specifically in cases when the task processing loop does not respond to the perturbations in the inlet steam temperature, thus allowing for setting up the loops’ controllers separately. In situations when the inlet steam temperature is experiencing perturbations, the impact of the lag on adjustment quality only becomes evident when the trajectory of the transition process shifts along the time scale by a lag value, which is completely in line with the Smith predictor principles. The system is focused on synthesizing the fuzzy logic rules and refining the parameters of the simulation used for adjustment purposes, based on the results of automated computer-aided control simulation. We propose a structural modification of the control system that makes it possible to compensate for any residual control errors caused by the non-linear structure of the fuzzy controller; this reduces the number of requirements for those set-up parameters where the value selection is based on the needs of simulation modeling, which requires a lot of computing resources. We demonstrate the results of simulation experiments that compare the efficiency of control using the system suggested and the efficiency of control using a system with a standard controller only. The computer simulation was performed in the MATLAB Simulink environment. We reaffirm that a combined control system performs better when adjusting the steam temperature.

Policy Capturing and Fuzzy Logic: A Better Approach to Representing Judgment Data?

2002 ◽  
Vol 46 (3) ◽  
pp. 541-545
Author(s):  
Amy E. Bolton ◽  
Randolph S. Astwood ◽  
Gwendolyn E. Campbell
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Traditional Approach ◽  
Value Added ◽  
Policy Capturing ◽  
Empirical Assessment ◽  
Alternative Approach ◽  
Modeling Techniques ◽  
The Impact ◽  
Judgment Data

At the 45th annual meeting of HFES, we conducted an alternative format session in which fuzzy logic was introduced as an alternative approach to analyzing judgment data and representing decision-making policies (see Buff et al., 2001). During the alternative format session, usability judgments were collected on-site for Advanced Distance Learning (ADL) applications. These data provided the basis for an empirical assessment of the value added of one modeling technique, fuzzy logic, over the more traditional approach to analyzing policy capturing data, multiple linear regression. This paper describes the results of an empirical assessment of the two modeling techniques. For a discussion of the empirical results of the impact of the different usability dimensions on the learning effectiveness of ADL applications, see Holness, Pharmer, and Buff (2002).

scholarly journals THE ROLE OF CREATIVITY IN ENTREPRENEURSHIP

2014 ◽  
Author(s):  
Maria Irina Dromereschi
Keyword(s):  
Decision Making ◽  
External Environment ◽  
Business Success ◽  
Self Confidence ◽  
High Level ◽  
The Impact ◽  
Entrepreneurial Factors

One of the most important factors to explain the sudden relevance of entrepreneurship, was the importance of creativity as a new source of competitiveness. Psychologists argue that being creative means to create something new, original and appropriate reality. Creative is characterized by originality and expressiveness, is imaginative, generative, pathfinder, invention, innovation etc. Increasing effects of globalization leads to the need creative approach in a market with a high level of opportunity and competition. Entrepreneurial factors overlap with many creative features such as curiosity, self-confidence, a high level of energy, responsibility and vision. As a highly complex mental formation, creativity is characterized by a multitude of ways such as productivity, usability, efficiency, value, ingenuity, innovation and originality. The impact of entrepreneurial creativity extends to the whole life of an entrepreneur, and not just during business. Success is stimulated by the use of juxtaposition and combination of different ideas that often but not related to the impact on decision making. Entrepreneurial Creativity should be seen as a competitive force and portfolio of skills. Adopting a creative entrepreneurial approach protects us from uncertainty and ambiguity in decision making in the external environment.

scholarly journals Minimal fuzzy microcontroller implementation for didactic applications

2003 ◽  
Vol 1 (02) ◽  
Author(s):  
F. Lara-Rojo ◽  
E. N. Sánchez ◽  
D. Zaldí­var-Navarro
Keyword(s):  
Developing Countries ◽  
Fuzzy Logic ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Low Cost ◽  
Level System ◽  
Teaching Tools ◽  
Software Development System ◽  
Fuzzy Techniques ◽  
Present Simulation

Fuzzy techniques have been successfully used in control in several fields, and engineers and researchers are today considering fuzzy logic algorithms in order to implement intelligent functions in embedded systems. We have started to develop a set of teaching tools to support our courses on intelligent control. Low cost implementations of didactic systems are particularly important in developing countries. In this paper we present the implementation of a minimal PD fuzzy four-rule algorithm in a lowcost 8-bit microcontroller, using a fuzzy logic software development system. On this ground we constructed a stand-alone fuzzy controller for a didactic liquid level system. We describe the methodology we followed, and present simulation and real time results of this controller.

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