scholarly journals Comparison of Energy Consumption in the Classical (PID) and Fuzzy Control of Foundry Resistance Furnace

2012 ◽  
Vol 12 (3) ◽  
pp. 129-132 ◽  
Author(s):  
E. Ziółkowskia ◽  
P. Śmierciak
Keyword(s):  
Energy Consumption ◽  
Fuzzy Control ◽  
Control Systems ◽  
Pid Controller ◽  
Large Time ◽  
Fuzzy Controller ◽  
Pid Controllers ◽  
Resistance Furnace ◽  
New Developments ◽  
Reduce Energy Consumption

Abstract Foundry resistance furnaces are thermal devices with a relatively large time delay in their response to a change in power parameters. Commonly used in automation classical PID controllers do not meet the requirements of high-quality control. Developed in recent years, fuzzy control theory is increasingly being used in various branches of economy and industry. Fuzzy controllers allow to introduce new developments in control systems of foundry furnaces as well. Correctly selected fuzzy controller can significantly reduce energy consumption in a controlled thermal process of heating equipment. The article presents a comparison of energy consumption by control system of foundry resistance furnace, equipped with either a PID controller or fuzzy controller optimally chosen.

Application of Fuzzy Control in Transformer Cooling System

2011 ◽  
Vol 383-390 ◽  
pp. 1262-1266
Author(s):  
Zhen Guo Jia
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Fuzzy Control ◽  
Fuzzy Controller ◽  
Cooling System ◽  
Lookup Table ◽  
Control Rules ◽  
Cooling Control ◽  
System Energy ◽  
Automation Level

Designed a device with PLC and inverter for transformer cooling control system. The structure of fuzzy controller is built with PLC. By calculating and testing, fuzzy and fuzzy control rules are established. Practical computing for the PLC to control the output lookup table is given. Using this technique, transformer cooling system energy consumption will be reduced, transformer’s coolers life will be extended and transformer cooling system automation level will be increased.

Optimal fuzzy control to reduce energy consumption in distillation columns

2005 ◽  
Vol 66 (2) ◽  
pp. 200-208 ◽  
Author(s):  
C. Bouyahiaoui ◽  
L. I. Grigoriev ◽  
F. Laaouad ◽  
A. Khelassi
Keyword(s):  
Energy Consumption ◽  
Fuzzy Control ◽  
Distillation Columns ◽  
Reduce Energy Consumption

Design and Application of Fuzzy Controller

2011 ◽  
Vol 464 ◽  
pp. 107-110 ◽  
Author(s):  
Wei Zhang ◽  
Xue Yong Li ◽  
Li Li ◽  
Jing Qiao Lv ◽  
Yan Feng Chen ◽  
...  
Keyword(s):  
Pid Controller ◽  
Large Time ◽  
Fuzzy Controller ◽  
Transient State ◽  
Pi Controller ◽  
Steam Temperature ◽  
Analysis And Design ◽  
Highly Nonlinear ◽  
Fuzzy Logic Method ◽  
Fuzzy Pi Controller

The steam temperature of the boiler is one of the important parameters in the power plant, and it is necessary to keep the temperature at a steady range. For the traditional PID controller, which is suitable for the analysis and design of the linear system, is unfit for the control of the steam temperature of the boiler, since it’s a nonlinear system where exists large time delay. To address this kind of problem, we combine the traditional PID method with the fuzzy logic method to construct a compound fuzzy PI controller in order to improve the performances in both steady state and transient state of the classical PID controller when highly nonlinear processes and better control performances have been arrived at.

scholarly journals Sampling Rate Impact on the Tuning of PID Controller Parameters

2016 ◽  
Vol 62 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Michal Laskawski ◽  
Miroslaw Wcislik
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Control Systems ◽  
Automatic Control System ◽  
Pid Controller ◽  
Sampling Rate ◽  
Sampling Period ◽  
Pid Controllers ◽  
Optimal Parameters ◽  
The Impact

Abstract The paper deals with an analysis of automatic control system with continuous and discrete PID controllers. A method of tuning the parameters of the continuous controller is presented, which is optimal according to the ITAE criterion. The behavior of control systems with discrete controllers whose parameters were tuned using the mentioned method are described. The impact of changes in the sampling period of controlled signal on the control quality is shown. Changes of the values of optimal parameters of discrete PID controllers in relation to changes of the sampling rate of controlled signal are characterized.

scholarly journals Study on Hybrid Fuzzy Controller Design by Model Reduction Method

2018 ◽  
Vol 7 (3.34) ◽  
pp. 558
Author(s):  
Joon Ho Cho ◽  
. .
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Performance Index ◽  
Delay Time ◽  
Pid Controller ◽  
Control Parameter ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Design Method ◽  
Reduced Model

Background/Objectives: In this paper, we proposed an improved model shrinking method and a hybrid-smith prediction fuzzy control design using a reduced model.Methods/Statistical analysis: The method of model reduction is based on Nyquist curve of frequency response, and the reduced model is obtained by considering the response of the transient state and the response of the steady state to the method. The proposed hybrid-smith prediction fuzzy controller tuning method was able to obtain the parameter value by utilizing a reduced model and using a genetic algorithm.Findings: The optimum PID controller design method using the reduced model applied a reduced model and a Smith prediction structure that compensates for the delay time in order to improve the control performance, and as a result, in order to minimize the performance index ITAE value I was able to design a controller. Here, the value of the control parameter was used by combining a method of directly obtaining the reduced model and a method of using the genetic algorithm by numerical analysis. In conclusion, the design method of the hybrid-smith Fuzzy control is a method of controlling by combining the PID controller, the Smith prediction compensating the delay time and the fuzzy controller in parallel, the value of the PID control parameter is optimized using the reduced model The value of the PID parameter was determined. The conversion coefficients (GE, GD, GH, GC) of Fuzzy control were obtained by applying genetic algorithm.Improvements/Applications: In the proposed method, it is possible to obtain directly the value of the parameter of the optimum PID controller and the value of the Smith prediction by using the reduced model, and the part of the Fuzzy conversion coefficient can be obtained by using the genetic algorithm , The ITAE performance index improved more than the conventional method.  

scholarly journals Investigation of the Possibility of Building a Neural Fuzzy Logic Controller with Discrete Terms for Controlling and Automating Oil and Gas Engineering Facilities

2021 ◽  
Vol 19 (3) ◽  
pp. 105-110
Author(s):  
A. M. Sagdatullin ◽  
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Control Systems ◽  
Fuzzy Logic Controller ◽  
Oil And Gas ◽  
Fuzzy Controller ◽  
Neuro Fuzzy ◽  
Classical Control

The issue of increasing the efficiency of functioning of classical control systems for technological processes and objects of oil and gas engineering is investigated. The relevance of this topic lies in the need to improve the quality of the control systems for the production and transportation of oil and gas. The purpose of the scientific work is to develop a neuro-fuzzy logic controller with discrete terms for the control and automation of pumping units and pumping stations. It is noted that fuzzy logic, neural network algorithms, together with control methods based on adaptation and synthesis of control objects, make it possible to learn the automation system and work under conditions of uncertainty. Methods for constructing classical control systems are studied, the advantages and disadvantages of fuzzy controllers, as the main control system, are analyzed. A method for constructing a control system based on a neuro-fuzzy controller with discrete terms in conditions of uncertainty and dynamic parameters of the process is proposed. The positive features of the proposed regulator include a combination of fuzzy reasoning about a technological object and mathematical predictive models, a fuzzy control system gains the possibility of subjective description based on neural network structures, as well as adaptation to the characteristics of the object. The graph of dependence for the term-set of the controlled parameter on the degree of membership is presented. A possible implementation of tracking the triggering of one of the rules of the neuro-fuzzy system in the format of functional block diagrams is presented. The process of forming an expert knowledge base in a neuro-fuzzy control system is considered. For analysis, a graph of the dependence of the output parameter values is shown. According to the results obtained, the deviation of the values for the model and the real process does not exceed 18%, which allows us to speak of a fairly stable operation of the neuro-fuzzy controller in automatic control systems.

Gyroscopic Coupling in Space Vehicle Attitude Control Systems

1962 ◽  
Vol 84 (1) ◽  
pp. 41-53 ◽  
Author(s):  
Robert H. Cannon
Keyword(s):  
Energy Consumption ◽  
Response Time ◽  
Control Systems ◽  
Strong Coupling ◽  
Attitude Control ◽  
Space Vehicle ◽  
Conventional System ◽  
Reduce Energy Consumption ◽  
Gyroscopic Coupling ◽  
And Control

The problem of controlling the attitude of a space vehicle is unusual in several respects. While the required precision may be extreme—less than 0.1 second of arc in certain cases—the required response time may often be very slow, measured in minutes or hours. Vehicles weighing tons may have to be controlled by inch-ounces of torque, and control energy is at an extreme premium. The present paper discusses the effects, on performance, of inter-axis coupling due to internal spinning parts. A de-coupling computer to nullify gyroscopic torque is described, and its utility is evaluated. The computer is found to improve precision, but to reduce energy consumption only in certain cases. It is shown that by postulating such a computer the performance of a given system may be accurately evaluated on the basis of much simpler single-axis relations, even though strong coupling is present. Specifically: (1) It is shown that the best available performance is established by postulating de-coupling control; and (2) a method is given for determining the amount by which a conventional system will fail to achieve that performance.

Investigation on Temperature and Humidity Control Fuzzy Self-Tuning PID Method

2011 ◽  
Vol 271-273 ◽  
pp. 1741-1746
Author(s):  
Jie Liu ◽  
En Ze Zhou ◽  
Yun Feng He ◽  
Xiao Jun Li
Keyword(s):  
Cold Storage ◽  
Large Time ◽  
Fuzzy Controller ◽  
Pid Controllers ◽  
Refrigeration System ◽  
Quality Of Control ◽  
Fuzzy Algorithms ◽  
Temperature And Humidity ◽  
Self Tuning

Because the cold storage refrigeration system has a the characteristics of large time delay, inertia and parameter variety , and conventional PID control can not realize the temperature and humidity coupling control, PID-fuzzy algorithms were developed and compared to conventional PID controllers, proving to be more suitable and reliable for a refrigerator used to foster needle mushroom. The thesis introduced the basic principle of the fuzzy control and present in detail the way to design Fuzzy Controller for temperature and humidity coupling control in Cold Storage refrigeration system .According to the simulate testing the cold storage refrigeration system with the SIMULINK of MATLAB, the control quality of the system and the ability of anti – jamming would have a great improvement and enhancement. When the PID-fuzzy algorithms were written in the PLC, the practical results show that this system has better stability, accuracy and quality of control.

Design of Locomotive Wiper Fuzzy Control System

2012 ◽  
Vol 538-541 ◽  
pp. 2999-3002
Author(s):  
Xiao Feng Huang ◽  
Yong Hong Long ◽  
Li He ◽  
Yang Fu Ou
Keyword(s):  
Fuzzy Control ◽  
Pid Controller ◽  
High Speed ◽  
Pulse Width Modulation ◽  
Fuzzy Controller ◽  
Control Unit ◽  
Fast Response ◽  
Low Noise ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

In order to optimize synchronization of wiper arm, a locomotive wiper controller of PWM and Fuzzy PID controller are proposed. The PWM controller is mainly designed of input control circuit, a central control unit, DC wiper motor pulse width modulation control and drive circuit, the motor stops the braking circuit, single-speed wiper motor of permanent magnet DC, etc. It can realize the high speed, low speed, intermission, stop function of wiper. The controller has values of stable performance, low noise, simple structure, etc. In locomotive wiper controller, Fuzzy PID controller combines the advantages of Fuzzy controller and PID controller, that it can achieve fast response, small overshoot. Fuzzy PID can also ensure the steady-state accuracy of the system, and the control performance is better than PID control and fuzzy control.

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