scholarly journals AN INTELLIGENT AIRCRAFT WINDOW SYSTEM FOR VISUAL COMFORT CONTROL

2021 ◽  
Author(s):  
Jasper Liu
Keyword(s):  
Fuzzy Logic ◽  
Automatic System ◽  
Fuzzy Logic Controller ◽  
Rate Of Change ◽  
Color Temperature ◽  
Visual Comfort ◽  
Simulated Sunlight ◽  
Window System ◽  
Set Up ◽  
Current Window

The purpose of this thesis is to develop an intelligent aircraft window system for visual comfort control based on electrochromic windows that can change the transparency depending on passenger’s needs and visual comfort. In the current window system, window transparency is controlled manually. The system developed in this thesis is an automatic system. Under this development, a mock-up is set up to mimic a section of cabin with an electrochromic window along with a simulated sunlight source and several light sensors. To measure visual comfort, the daylight glare index (DGI) is adopted. Based on DGI, a fuzzy logic classifier is developed to evaluate visual comfort/discomfort. This is followed by developing a fuzzy logic controller that can automatically adjust the window transparency based on the measured DGI level and the rate of change of DGI. DGI set point for different individuals, the effect of illuminance and color temperature are also discussed

scholarly journals AN INTELLIGENT AIRCRAFT WINDOW SYSTEM FOR VISUAL COMFORT CONTROL

2021 ◽  
Author(s):  
Jasper Liu
Keyword(s):  
Fuzzy Logic ◽  
Automatic System ◽  
Fuzzy Logic Controller ◽  
Rate Of Change ◽  
Color Temperature ◽  
Visual Comfort ◽  
Simulated Sunlight ◽  
Window System ◽  
Set Up ◽  
Current Window

The purpose of this thesis is to develop an intelligent aircraft window system for visual comfort control based on electrochromic windows that can change the transparency depending on passenger’s needs and visual comfort. In the current window system, window transparency is controlled manually. The system developed in this thesis is an automatic system. Under this development, a mock-up is set up to mimic a section of cabin with an electrochromic window along with a simulated sunlight source and several light sensors. To measure visual comfort, the daylight glare index (DGI) is adopted. Based on DGI, a fuzzy logic classifier is developed to evaluate visual comfort/discomfort. This is followed by developing a fuzzy logic controller that can automatically adjust the window transparency based on the measured DGI level and the rate of change of DGI. DGI set point for different individuals, the effect of illuminance and color temperature are also discussed

Artificial Neural Networks Used As a Rule Selector for Fuzzy Logic Controllers

1993 ◽  
Author(s):  
Shou-Heng Huang ◽  
Ron M. Nelson
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Operating Conditions ◽  
Delta Rule ◽  
Rule Sets ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Set Up ◽  
And Control

Abstract A feedforward, three-layer, partially-connected artificial neural network (ANN) is proposed to be used as a rule selector for a rule-based fuzzy logic controller. This will allow the controller to adapt to various control modes and operating conditions for different plants. A principal advantage of an ANN over a look up table is that the ANN can make good estimates to fill in for missing data. The control modes, operating conditions, and control rule sets are encoded into binary numbers as the inputs and outputs for the ANN. The General Delta Rule is used in the backpropagation learning process to update the ANN weights. The proposed ANN has a simple topological structure and results in a simple analysis and relatively easy implementation. The average square error and the maximal absolute error are used to judge if the correct connections between neurons are set up. Computer simulations are used to demonstrate the effectiveness of this ANN as a rule selector.

Fuzzy Logic Control of a Laboratory Magnetic Levitation System

2003 ◽  
Author(s):  
V. Ram Mohan Parimi ◽  
Piyush Jain ◽  
Devendra P. Garg
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Magnetic Levitation ◽  
Rate Of Change ◽  
Control Laboratory ◽  
Logic Control ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
And Control

This paper deals with the Fuzzy Logic control of a Magnetic Levitation system [1] available in the Robotics and Control Laboratory at Duke University. The laboratory Magnetic Levitation system primarily consists of a metallic ball, an electromagnet and an infrared optical sensor. The objective of the control experiment is to balance the metallic ball in a magnetic field at a desired position against gravity. The dynamics and control complexity of the system makes it an ideal control laboratory experiment. The student can design their own control schemes and/or change the parameters on the existing control modes supplied with the Magnetic Levitation system, and evaluate and compare their performances. In the process, they overcome challenges such as designing various control techniques, choose which specific control strategy to use, and learn how to optimize it. A Fuzzy Logic control scheme was designed and implemented to control the Magnetic Levitation system. Position and rate of change of position were the inputs to Fuzzy Logic Controller. Experiments were performed on the existing Magnetic Levitation system. Results from these experiments and digital simulation are presented in the paper.

Anti-Swing Trajectory Control of an Overhead Crane

2011 ◽  
Author(s):  
E. H. K. Fung ◽  
H. F. Yu ◽  
K. H. Suen ◽  
A. T. Leung
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Equations Of Motion ◽  
Overhead Crane ◽  
Transportation Time ◽  
Swing Angle ◽  
Total Potential ◽  
Logic Control ◽  
Set Up

Imprecise positioning and swing of load of overhead crane cause prolonged transportation time. Some researchers tried to achieve suppression of swing angle and fast transfer simultaneously. But, the hoisting motion is usually ignored which can cause greater swing angle. Hence, a physical 2-DOF overhead crane model which consists of horizontal motion and hoisting motion is set up for this study. The total kinetic energy and the total potential energy are derived to obtain dynamic equations of motion by using Lagrangian method. Secondly, fuzzy logic control (FLC) has been adopted to control positioning of horizontal and hoisting motion and to suppress swing angle during transportation. Moreover, to minimize total transportation time, proportional (P) controller is added to the system forming the switching P+FLC controller. Finally, the proposed methods are evaluated by simulations and experiments. The overall results show that fuzzy logic controller combined with P controller (P+FLC) can effectively reduce the transportation time with a little increase in the swing angle.

scholarly journals Optimization of Fuzzy Logic Controller for Supervisory Power System Stabilizers

10.14311/1518 ◽  
2012 ◽  
Vol 52 (2) ◽  
Author(s):  
Y. A. Al-Turki ◽  
A.-F. Attia ◽  
H. F. Soliman
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Set ◽  
Fuzzy Logic Controller ◽  
Fuzzy Model ◽  
Rate Of Change ◽  
Computational Time ◽  
Adaptive Fuzzy ◽  
Wide Range ◽  
Adaptive Fuzzy Logic

This paper presents a powerful supervisory power system stabilizer (PSS) using an adaptive fuzzy logic controller driven by an adaptive fuzzy set (AFS). The system under study consists of two synchronous generators, each fitted with a PSS, which are connected via double transmission lines. Different types of PSS-controller techniques are considered. The proposed genetic adaptive fuzzy logic controller (GAFLC)-PSS, using 25 rules, is compared with a static fuzzy logic controller (SFLC) driven by a fixed fuzzy set (FFS) which has 49 rules. Both fuzzy logic controller (FLC) algorithms utilize the speed error and its rate of change as an input vector. The adaptive FLC algorithm uses a genetic algorithmto tune the parameters of the fuzzy set of each PSS. The FLC’s are simulated and tested when the system is subjected to different disturbances under a wide range of operating points. The proposed GAFLC using AFS reduced the computational time of the FLC, where the number of rules is reduced from 49 to 25 rules. In addition, the proposed adaptive FLC driven by a genetic algorithm also reduced the complexity of the fuzzy model, while achieving a good dynamic response of the system under study.

Varying the Stiffness of a Beam-Like Neutralizer Under Fuzzy Logic Control

2001 ◽  
Vol 124 (1) ◽  
pp. 90-99 ◽  
Author(s):  
M. R. F. Kidner ◽  
M. J. Brennan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Excitation Frequency ◽  
Rate Of Change ◽  
Single Frequency ◽  
Logic Control ◽  
Excitation Period ◽  
Simulation And Experiment ◽  
Proportional Controller ◽  
Second Period

Vibration neutralizers are effective vibration control devices at a single frequency. If they can compensate for drift in the excitation frequency by adjusting their stiffness the performance can be improved, and the range of problems to which they can be applied is broadened. This paper considers a beam-like adaptive vibration neutralizer, and it is shown that the stiffness of the device and hence its natural frequency can be significantly altered by varying the beam cross-section. Several different beam configurations are investigated and the rate of change of stiffness as a function of beam separation is calculated for each configuration. The results are validated by some simple experiments. Real-time stiffness control of a beam-like tuneable neutralizer is also demonstrated both by computer simulation and experiment. The neutralizer is subjected to swept sine excitation over a six-second period and the tuned condition is maintained throughout the excitation period. The efficacy of using a nonlinear fuzzy logic controller is compared with the use of a simple proportional controller.

scholarly journals Design of a semi-autonomous modular robotic vehicle for gas pipeline inspection

2003 ◽  
Vol 217 (2) ◽  
pp. 109-122 ◽  
Author(s):  
J K Ong ◽  
D Kerr ◽  
K Bouazza-Marouf
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Autonomous Vehicle ◽  
Robotic System ◽  
Rate Of Change ◽  
Control Technique ◽  
Background Information ◽  
Pipe System ◽  
Robotic Vehicle ◽  
Proprioceptive Sensors

This paper presents a new solution for inspecting and repairing defects in live gas pipelines. The proposed approach is the development of a modular and semi-autonomous vehicle system. The robotic system has a drive mechanism, capable of navigating and adjusting its orientation in various configurations of pipelines. Other features of the system are cable-free communications, semi-autonomous motion control as well as integration of sensory devices. The robotic system is designed to traverse in 150–300 mm diameter pipes through straight and curved sections, junctions and reducers. The vehicle control and navigation technique is implemented using a two-mode controller consisting of a proportional-integral-derivative (PID) and fuzzy logic control. Unlike other available systems, the vehicle employs proprioceptive sensors to monitor its own states. The fuzzy logic controller is used to evaluate the sensor outputs such as speed, climbing angle and rate of change of climbing angle. This control technique allows the vehicle to drive and adapt in a partially observable gas pipe system. Laboratory experiment results are presented. The paper also describes a cable-free communication method for the system. A brief account of typical pipe environments and currently available inspection tools is presented as background information.

scholarly journals Three-phase Three-level Inverter Grid-tied PV System with Fuzzy Logic Control based MPPT

2018 ◽  
Vol 3 (3) ◽  
pp. 96-105
Author(s):  
Yacine AYACHI AMOR ◽  
Frid HAMOUDI ◽  
Aissa KHELDOUN
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Rate Of Change ◽  
Maximum Power ◽  
International Standards ◽  
Solar Array ◽  
Pv System ◽  
Climate Conditions ◽  
Point Tracking ◽  
Three Phase

This paper presents a three phase single stage grid connected photovoltaic PV system. Maximum power transfer from the solar array to grid is ensured by using fuzzy logic (FL) based maximum power point tracking (MPPT) controller. The proposed MPPT technique provides fast and high performances under variable climate conditions as well as sudden variation of irradiance level. Change of measured photovoltaic power and its rate of change are the input variables of the proposed fuzzy logic controller while the change in reference current is defined as the output variable. In order to meet the power quality required by the international standards, a Space Vector Modulation (SVM) controlled three-level T-type inverter and a series LCL filter are used. To show the effectiveness of the proposed grid-connected system, Matlab/Simulink software is used to carry out the simulation part. Obtained results show the role of each component, particularly the response of the maximum power tracking, the quality of the injected power, the unity power factor operation and the system’s efficiency.

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

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