scholarly journals The Application of a Neuro-Fuzzy Adaptive Crane Control System

2010 ◽  
Vol 14-15 (1) ◽  
pp. 247-258
Author(s):  
Jarosław Smoczek ◽  
Janusz Szpytko
Keyword(s):  
Control System ◽  
Material Handling ◽  
Fuzzy Controller ◽  
Laboratory Model ◽  
Crane Control ◽  
Neuro Fuzzy ◽  
To Come ◽  
Fuzzy Control Algorithm ◽  
Fuzzy Adaptive

The Application of a Neuro-Fuzzy Adaptive Crane Control SystemThe unconventional methods, mostly based on fuzzy logic, are often addressed to a problem of anti-sway crane control. The problem of practical application of those solutions is important owing to come the growing expectations for time and precision of transportation operations and exploitation quality of material handling devices. The paper presents the designing methods of an adaptive anti-sway crane control system based on the neuro-fuzzy controller, as well as the software and hardware equipments used to aid the programming realization the fuzzy control algorithm on a programmable logic controller (PLC). The proposed application of control system was tested on the laboratory model of an overhead traveling crane.

scholarly journals The Fuzzy Robust Anti-Sway Crane Control System

2009 ◽  
Vol 9-10 (1) ◽  
pp. 87-98
Author(s):  
Jarosław Smoczek ◽  
Janusz Szpytko
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
Pole Placement ◽  
Laboratory Model ◽  
Robust Controller ◽  
Minimal Set ◽  
Inference System ◽  
Crane Control ◽  
Takagi Sugeno ◽  
Operating Points

The Fuzzy Robust Anti-Sway Crane Control SystemThe paper presents the pole placement approach to solve problem of conventional, based of proportional-derivative controllers, as well as robust, based of fuzzy controller, anti-sway crane control. The methods of robust gain-scheduling crane control system and selecting minimal set of operating points were shown. The fuzzy robust controller, based of Takagi-Sugeno-Kang inference system, was presented, as well as results of experiments, carried out using laboratory model of an overhead traveling crane, were shown in the paper.

The Design of Bending Force Shape Control System Based on Fuzzy Adaptive Control

2014 ◽  
Vol 945-949 ◽  
pp. 2794-2798
Author(s):  
Jun Shuang Ma
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Shape Control ◽  
Fuzzy Controller ◽  
Control Performance ◽  
Steel Shape ◽  
On Line ◽  
And Control ◽  
Fuzzy Adaptive

This paper presents a fuzzy adaptive shape control system, which overcomes the shortcoming of simple PID controller and simple fuzzy controller. The PID parameters can be adjusted on-line in this system. The simulation result shows that the control system can improve the control performance and control quality of steel shape control.

The neuro-fuzzy adaptive anti-sway crane control system

2009 ◽  
Vol 42 (15) ◽  
pp. 58-63 ◽  
Author(s):  
Jarosław Smoczek ◽  
Janusz Szpytko
Keyword(s):  
Control System ◽  
Crane Control ◽  
Neuro Fuzzy ◽  
Fuzzy Adaptive

scholarly journals An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Mechanical Design ◽  
Mechanical Ventilator ◽  
Mechanical Ventilators ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.

A Neuro-Fuzzy Controller for Compensation of Voltage Disturbance in SMIB System

2017 ◽  
Vol 5 (1) ◽  
pp. 72
Author(s):  
Budi Srinivasarao ◽  
G. Sreenivasan ◽  
Swathi Sharma
Keyword(s):  
Power Quality ◽  
Power Distribution ◽  
Fuzzy Controller ◽  
Quality Issue ◽  
Simulink Model ◽  
Neuro Fuzzy ◽  
Current Voltage ◽  
Control Circuits ◽  
Electrical Loads

Since last decade, due to advancement in technology and increasing in the electrical loads and also due to complexity of the devices the quality of power distribution is decreases. A Power quality issue is nothing but distortions in current, voltage and frequency that affect the end user equipment or disoperation; these are main problems of power quality so compensation for these problems by DPFC is presented in this paper. The control circuits for DPFC are designed by using line currents, series reference voltages and these are controlled by conventional Neuro-Fuzzy controllers. The results are observed by MATLAB/SIMULINK model.

Fuzzy Adaptive Control of Airborne Electro-Optical Tracking Systems Based on Variable Universe

2011 ◽  
Vol 383-390 ◽  
pp. 5972-5977
Author(s):  
Song Gao ◽  
Xiao Xia Xu ◽  
Qin Kun Xiao ◽  
Quan Pan
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Dynamic Performance ◽  
Optical Tracking ◽  
Control Performance ◽  
Tracking Systems ◽  
Variable Universe ◽  
Fuzzy Control Algorithm ◽  
Fuzzy Adaptive

In order to improve the control performance of airborne EO tracking systems, we develop a proposed variable universe control algorithm based on fuzzy reasoning. The algorithm combines a new fuzzy control algorithm with classic PID control algorithm and greatly improves the dynamic performance of the airborne EO tracking systems. The simulation results indicate that the adaptive fuzzy controller can ensure the precision of the system with better adaptability and robustness.

Interval arithmetic-based fuzzy discrete-time crane control scheme design

2013 ◽  
Vol 61 (4) ◽  
pp. 863-870 ◽  
Author(s):  
J. Smoczek
Keyword(s):  
Control System ◽  
Discrete Time ◽  
Interval Arithmetic ◽  
Material Handling ◽  
Closed Loop ◽  
Container Terminals ◽  
Crane Control ◽  
Loop Control ◽  
Fuzzy Interpolation ◽  
Polynomial Coefficients

Abstract In many manufacturing segments, container terminals and shipping yards the automation of material handling systems is an important element of enhancing productivity, safety and efficiency. The fast, precise and safe transfer of goods in crane operations requires a control application solving the problems, including non-collision trajectory planning and limitation of payload oscillations. The paper presents the interval arithmetic-based method of designing a discrete-time closed-loop anti-sway crane control system based on the fuzzy interpolation of linear controller parameters. The interval analysis of a closed-loop control system characteristic polynomial coefficients deviation from their nominal values is proposed to define a minimum number of fuzzy sets on the scheduling variables universe of discourse and to determine the distribution of triangular-shaped membership functions parameters, which satisfy the acceptable range of performances deterioration in the presence of the system’s parameters variation. The effectiveness of this method was proved in experiments conducted using the PAC system on the laboratory scaled overhead crane.

Research of Temperature Control System Based on Fuzzy Control Algorithm for Mixer

2009 ◽  
Vol 87-88 ◽  
pp. 288-292 ◽  
Author(s):  
Chuan Sheng Wang ◽  
Fu Hai Zhou
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Cooling Water ◽  
Host Computer ◽  
Temperature Control System ◽  
Control Value ◽  
Fuzzy Control Algorithm

The changes of temperature in the rubber mixing process is of great significance. How to ensure the changes of temperature in rubber mixing is an important issue. The article introduces the temperature control system based on the fuzzy control algorithm. Using the host computer as the fuzzy controller, and the host computer educes the control value based on the difference between the reference input and the measure value. The system automatically discharges of high temperature water and automatically adds the appropriate amount of cooling water. The system can ensure the stability of the mixing temperature and ensure the quality of rubber mixing.

PID Parameter Setting Based on Fuzzy Control Algorithm and its Application in the Temperature Control System of Airplane

2012 ◽  
Vol 588-589 ◽  
pp. 1503-1506
Author(s):  
Fang Ding ◽  
Tao Ma
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Temperature Control ◽  
Control Algorithm ◽  
Control Method ◽  
Fuzzy Controller ◽  
Temperature Control System ◽  
System Control ◽  
Control Effect ◽  
Fuzzy Control Algorithm

This Temperature control system of aircraft cabin is a complex system with nonlinear, time-varying, model inaccurate and work environment uncertain. According to the system control requirements, the fuzzy controller with the characteristic of fast response speed, good stability and strong resistance to interference is used in the study. The system error is adjusted constantly by using fuzzy control algorithm and simulation study is conducted in the software Matlab. The results are showed that control effect of control method used in this study is better than the traditional PID control method, and dynamic performance, steady state accuracy and robustness of system is effectively improved.

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