Fuzzy chatGPT down

Mathematical Problems in Engineering

This paper presents the development of a virtual didactic tool for students of mechatronic engineering taking an intelligent system course. The objective of the tool is for students to learn the structures for fuzzy control systems. This tool makes it easier for students to understand the behavior of the membership functions of input and output variables, the evaluation of the set of fuzzy rules, and the method of defuzzification, giving the students the possibility of applying a fuzzy controller in industrial processes using a data acquisition board. The proposed tool was developed with the virtual instrumentation software LabVIEW. It has the advantage that students can manipulate the internal structure of the fuzzy logic control system in a unique window where students can analyze the behavior of internal signals by looking at the response graphs. The fuzzy controller can be easily translated to a real application by using LabVIEW compatible hardware. To have feedback from student...

2004 Annual Conference Proceedings

The Intelligent Fuzzy Controllers Laboratory has been developed in the Department of Electrical and Computer Engineering of Western Michigan University with the help of a DURIP grant by the Department of Defense [6] and generous donations by ABB Automation Technology Products. This new lab is to support research, the development of advanced courses, and graduate projects in the area of intelligent controls for large, complex hybrid systems. One of the targeted applications is the supervisory level of flatness control for cold rolling mills. Contemporary industrial control systems are designed using Object Oriented methods and software agents. It is required that the system should reach its goals even when unexpected events occur in an uncertain environment. The current research focus is on fault detection and automated recovery from faults. A fuzzy automaton has been proposed to model the system at critical junctions of the control algorithm. A research project is currently underway to develop a Generic Encapsulated Fuzzy Automaton Software Agent for Object Oriented Control Systems. The aim of the project is twofold: 1) to develop and evaluate the performance of new methods and architectures for this area of research, and 2) to create a laboratory environment in which masters and doctoral students can work on independent projects as well as course assignments.

2000

This paper deals with the necessity of changing the current approach to teaching mathematics and new, fuzzy control based models in higher education in engineer training, mainly based on the experiences gained at the Polytechnical Engineering College of Subotica.

The underlying technologies of chatbot technology-artificial intelligence and machine learning-ensure that both their capabilities and knowledge bases will continue to develop. The advancement of higher education in India, however, may surely be significantly impacted by technology and AI. Modern artificial intelligence (AI) algorithms are used by ChatGPT, which enables it to understand natural language and respond accordingly. Cutting-edge technology is used by ChatGPT. Together, teachers and students can use this innovative approach to learning. The traditional methods of schooling are no longer successful in our 21st-century environment. The use of ChatGPT makes it possible to achieve many of the goals of the Indian higher education system.

The most important feature of the intelligent tutoring systems (ITS), one of the most popular study topics of recent years, is that it provides an opportunity for individual learning by taking students' individual differences into account. In order to be able to realize this feature, it is necessary that the system recognizes students well. The process of recognizing student is performed as a result of observations which ITS applies on students. A number of uncertainties arise during these observations. In order to minimize learning uncertainties and create a productive and effective ITS, type-2 fuzzy logic, one of the artificial intelligence techniques, is used in the system developed in this study. In order to show the effectiveness of the developed web-based ITS, it is applied to the teaching of a basic Control Course. The educational evaluation of the system is presented in the paper.

Applied Sciences, 2020

This research focused on developing a methodology that facilitates the learning of control engineering students, specifically developing skills to design a complete control loop using fuzzy logic. The plant for this control loop is a direct current motor, one of the most common actuators used by educational and professional engineers. The research was carried out on a platform developed by a group of students. Although the learning techniques for the design and implementation of controllers are extensive, there has been a delay in teaching techniques that are relatively new compared to conventional control techniques. Then, the hands-on laboratory offers a tool for students to acquire the necessary skills in driver tuning. In addition to the study of complete systems, the ability to work in a team is developed, a fundamental skill in the professional industrial area. A qualitative and quantitative analysis of student learning was carried out, integrating a multidisciplinary project based on modern tools.

IEEE Transactions on Education, 2002

Computer Applications in Engineering Education, 2010

Fuzzy system technologies are of emerging interest in the specification and implementation of complex systems. This article introduces fuzzy instructional planner, which models the tutor module in a intelligent tutorial system (ITS). The behaviour of this system is defined by strategies which adapt the learning process for individual students by applying appropriate pedagogical methodologies. For this reason, the purpose of a instructional planner is to mimic the behaviour of the teacher able to control learning process satisfactorily. The knowledge acquisition is based on the reasoning carried out by the teacher in a learning process. Usually, this information is obtained from human expert who supplied linguistic information. The capacity to use linguistic information is specific to fuzzy inference systems. ß

Design of a fuzzy controller requires more design decisions than usual, for example regarding rule base, inference engine, defuzzification, and data pre-and post processing. This tutorial paper identifies and describes the design choices related to single-loop fuzzy control, based on an international standard which is underway. The paper contains also a design approach, which uses a PID controller as a starting point. A design engineer can view the paper as an introduction to fuzzy controller design.

Diagnostyka

The paper represents laboratory bench to analyse a system of automated control with a fuzzy controller. The laboratory bench consists of a thermal object, and software and hardware complex involving logic controller VIPA System 200 V as well as HMI / SCADA system Zenon Supervisor 7.0. The thermal object is described with the help of the second-order differential equation using "current value within the power converter of electric heater-air temperature inside a thermal object" control channel. Coefficients of the differential equation depend upon location of a dampener and upon rotation frequency of a centrifugal fan. Control error (ie deviation between the specified temperature value within the thermal object and its current value), and derivative of the error, represented in the form of linguistic variables involving five triangular terms and two trapezoidal (extreme) ones have been used as the input values of the fuzzy controller. Output value of the fuzzy controller is the electric power supplied to the electric heater and assuming seven specified values. Selection of the specific value of electric power depends upon knowledge base being a finite set of rules of fuzzy sets falling into line with the applied linguistic variables. To implement such a system of automated control with a fuzzy controller, original software has been developed making it possible to analyze a process of thermal object heating with the use of human-computer interface. Interaction algorithm of certain program elements has been described. Experimental results, concerning the thermal object transfer from different initial conditions to terminal ones, have been demonstrated. A dependence of mean-square error of the controlled value upon the control period has been demonstrated.