An educational tool for fuzzy logic controller and classical controllers

This research was conducted within the framework of a National Science Foundation sponsored summer Research Experience for Undergraduate (REU) students. This research considers small-scale and mathematical models of simple one-story structures that are subjected to free and base-motion excitations and installed with and without passive damping devices to gain an understanding of their dynamic behavior while reviewing active and semi-active damping means being applied and researched today. Using computer programming and numerical methods, the goal is to understand and counteract catastrophic disasters to structures caused by earthquakes. The research is broken down into a number of MATLAB simulations and experiments in order to understand basic dynamic and control features required to design earthquake resilient buildings. These experiments include free vibration experiments to test for the stiffness of columns for different heights and to test for the natural frequency and damping ratio of a one-story structure under different mass loads. Active PD control was then applied to an experimental system experiencing accelerations attributed to the Northridge 1994, Kobe 1995, El Centro 1940, and Mendocino 1992 earthquakes. Robustness comparisons were made between (1) P control; (2) D control; and (3) PD control for the above earthquake inputs to the shaker. A fuzzy logic controller was developed to effectively control transient vibrations. The uniqueness of this control concept is that the fuzzy control continuously varies the damping characteristics of a semi-active tuned mass damper (TMD). It was concluded that a fuzzy logic based TMD was more effective than a regular passive TMD, by providing half the settling times. ß

Section: Introductionmentioning

confidence: 98%

PD and fuzzy logic control for earthquake resilient structures

Álvarez

McElwain

Thesing

et al. 2012

“…Based on this, Deschênes and Pomerleau [11] developed a simulator for process control education with a case study of a mixing process. Also Akcayol et al [12] presented a tool to teach fuzzy logic controller and compare to classical ones to undergraduate and graduate level students.…”

Section: Introductionmentioning

confidence: 98%

Educational simulator for multicomponent distillation research and teaching in chemical engineering

Mendes

Marangoni

Meneguelo

et al. 2009

“…Akcayol et al [9] describe the development of an educational tool for fuzzy logic controllers and classical controllers, aimed for undergraduate and graduate level students. The tool was designed with the aim that students could establish a thorough understanding and be able to compare the fuzzy logic controllers with classical controllers.…”

Section: Introductionmentioning

confidence: 99%

An undergraduate fuzzy logic control lab using a line following robot

İbrahim

Alshanableh

2011

Fuzzy logic controllers have gained popularity in the past few decades with highly successful implementation in many fields. Fuzzy logic enables designers to control complex systems more effectively than traditional methods. Teaching students fuzzy logic in a laboratory can be a time-consuming and an expensive task. This paper presents a low-cost educational microcontroller-based tool for fuzzy logic controlled line following mobile robot. The robot is used in the second year of undergraduate teaching in an elective course in the department of computer engineering of the Near East University. Hardware details of the robot and the software implementing the fuzzy logic control algorithm are given in the paper. ß