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1994, Springer eBooks
As it knows most of the quotidian types of control, problems are not simply to evaluate and considerate formal modelling based in traditional techniques. The process control makes the evaluation and executions more efficient in the industry. This article was made with the purpose to compare two types of control, one with FUZZY logic and second one PID control. Here we have developed temperature control system using fuzzy logic. The flyback converter with voltage doubler rectifier acts as an output module. To overcome the efficiency degradation during lightload due to load dependent soft switching of the ZVS, a control method using pulse width modulation (PWM)proportional to the load current is used. Comparison between Fuzzy logic controller & PID controller based on pulse width modulation is proposed and the results are analyzed. Thus comparing the result PID controller gives more accurate results than first Fuzzy logic controller.
International Journal of Scientific Research in Science, Engineering and Technology, 2019
As it knows most of the quotidian types of control, problems are not simply to evaluate and considerate formal modelling based in traditional techniques. The process control makes the evaluation and executions more efficient in the industry. This article was made with the purpose to compare two types of control, one with FUZZY logic and second one PID control. Here we have developed temperature control system using fuzzy logic. The flyback converter with voltage doubler rectifier acts as an output module. To overcome the efficiency degradation during lightload due to load dependent soft switching of the ZVS, a control method using pulse width modulation (PWM)proportional to the load current is us Comparison between Fuzzy logic controller & PID controller based on pulse width modulation is proposed and the results are analysed. Thus, comparing the result PID controller gives more accurate results than first Fuzzy logic controller.
World Academy of Research in Science and Engineering , 2020
This paper is meant to highlight and discuss the facts and uses of fuzzy logic in terms of a temperature controller. The purpose of this temperature control system is to heat a room to a specified temperature then tries to maintain it at that temperature in a controlled manner. This paper will highlight different possible concerns done in the system and possible solutions to this fuzzy logic pattern. The applications are far-reaching as the temperature control can be depicted and used in multiple control systems such as control temperature in air conditioning units, generators, temperature for aquariums, etc. All these applications with fuzzy logic can help dictate the amount of energy used constantly to save power while achieving the needed amount. The fuzzy logic in temperature control systems can vary and the truth table for the logic system may vary widely as well. However, the main point of the system is to create and apply control correctly. By making use of built-in functions that can potentially correct errors and predict patterns in terms of date and time of the year, the time of the day and the flow of air, etc. It can effectively correct and make adjustments for the temperature correctness.
In this paper, the uncontrolled single area Load Frequency Control system is modelled using state space representation. Output response of the system which is frequency deviation is simulated in MATLAB. Adaptive Fuzzy Logic (FL) controller combined with Proportional Integral (PI) controlleris added to the uncontrolled system using SIMULINK and MATLAB Fuzzy Inference System. The effect of the combined control on the system output response is measured in terms of undershoot percentage, settling time, and frequency error. By comparing the simulations of uncontrolled and controlled system, it can be concluded that Adaptive FL controller combined with conventional PI controller is the most efficient, reliable, and robust control to solve power system control problem. The proposed control improves transient and steady state behavior of the system.
2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation, 2010
This paper describes the design and analysis of a closed loop Fuzzy Logic Controller for temperature control system of a gas pilot plant. The overall model is built in MATLAB/Simulink-technical computing software that has adjustable structures where variables for the model and control strategies can be modified. Simulations have been performed for both controllers to observe the response. Results of the PI-Fuzzy Controller are compared with the response of the conventional PID controller. The PID controller response using Ziegler Nichols open loop, Ziegler Nichols closed loop and Cohen Coon method are presented and evaluated against the response of 3, 5, 7 and 9 membership functions of the PI-fuzzy Controller.
The aim of the temperature c ontrol is to heat the system up to delimitated temperature, afterwardhold it at that temperature in insured manner. Fuzzy Logic Controller (FLC) is best way in which this type of precision control can be accomplished b y controller. During past twenty yearssignificant amount of research using fuzzy logic has done in this field of control of non - linear dynamical system. Here we have developed temperature control system using fuzzy logic. Control theory techniques are the root from which convention controllers are deducted . The desired response of the output can be guarante ed by the feedback controller .
AIP Conference Proceedings
In recent years, there has been a need to design highly efficient cooling devices that are used in the manufacture of nanomaterials and some medical treatments. The objective of this paper is to design the membership shape of a variable speed cycle variable speed fuzzy logic controller for a cooling engine. The fuzzy logic controller sets the sampling time for the SVPWM in the inverter system in the variable speed drive cooling cycle. The research focuses on the systematic design of membership ranges for key design factors such as control error and control error rate. The upper and lower limits of the membership ranges are prepared from the static characteristics data obtained by modelling MATLAB. Membership range was tested on control error and error rate control experiments. The effect of sampling time on control performance has been investigated and has been shown to have a significant effect on the refrigeration cycle control performance of a variable speed drive, the results of proposed device demonstrate settling time less than (15 sec).
Ieee Transactions on Industry Applications, 2002
A closed-loop control system incorporating fuzzy logic has been developed for a class of industrial temperature control problems. A unique fuzzy logic controller (FLC) structure with an efficient realization and a small rule base that can be easily implemented in existing industrial controllers was proposed. The potential of FLC in both software simulation and hardware test in an industrial setting was demonstrated. This includes compensating for thermo mass changes in the system, dealing with unknown and variable delays, operating at very different temperature set points without retuning, etc. It is achieved by implementing, in the FLC, a classical control strategy and an adaptation mechanism to compensate for the dynamic changes in the system. The proposed FLC was applied to two different temperature processes and performance and robustness improvements were observed in both cases. Furthermore, the stability of the FLC is investigated and a safeguard is established.
Journal of Electrical & Electronic Systems Research
This paper focuses on the modeling, development, and implementation of a Fuzzy PID controller in controlling the heating system. This study will look into the effectiveness of a fuzzy Proportional Integral Derivative (PID) control scheme for this application. Instead of using a trial-and-error method for the controller tuning, this study proposes a fuzzy PID control to tune the controller parameters and to improve the conventional PID controller transient response. Modeling of the PT326 heating system is required before designing the controller. Through the MATLAB System Identification Toolbox, a discrete-time model is obtained and represented by an ARX model structure. A simulation study had been implemented on a unit step input. The results demonstrated that the system shows positive improvement in terms of rise time and settling time when fuzzy PID controller was applied.
—To solve equipment problems related to the failure of air conditioning units in VFD (Variable Frequency Drive) rooms to restart after interruptions in the power supply, this paper introduces a hardware and software design based on the constant temperature system of STC89C52 SCM and carries out the simulation through MATLAB to compare and analyze the fuzzy self-turning PID control results and traditional PID control simulation results. The experimental results show that this design can realize the SCM constant temperature control of a fuzzy PID algorithm.
This paper outlines the proposal for the design of an intelligent electronic thermostat that achieves control by means of fuzzy logic, with the view of bringing about greater comfort by imitating human reasoning, and more efficient utilization of power. A cheap low cost microcontroller would be used for the implementation of this design. Ambient conditions that influence the perception of temperature serve as inputs to the thermostat and the output is automated and put into effect in temperature adjustment. Program development is to be broken into five parts namely fuzzification, inference, composition and defuzzification and this will be carried out using Inform® software FuzzyTECH®. Automatic decision making of the controller is based on a set of rules generated by the program. After specifying the relationship between the inputs and outputs, a certain number of rules will be generated on which to base decision- making. The number of rules is likely to be high, which will make dec...
Energy Conversion and Management, 2006
Nowadays, instead of conventional control techniques, modern control techniques have been implemented for a lot of industrial models practically or theoretically. In this study, a fuzzy logic-based control technique to regulate the power and enthalpy outputs in a boiler of a 765 MW coal-fired thermal power plant was carried out. For comparison, a conventional proportional, integral and derivative (PID), a fuzzy logic (FL) and a fuzzy gain scheduled proportional and integral (FGPI) controllers have been applied to the power plant model. The simulation results show that the FGPI controller developed in this study performs better than the rest controllers on the settling time and overshoot of power and enthalpy outputs.
2020
Furnace temperature controller has a large overshoot and constant oscillation error. To solve this problem there are several studies done on the PID type furnace temperature controller with different PID parameters, but this method is not efficient because of the nonlinearity of temperature. Due to this reason, the overshoot happens and steady-state errors are observed. Other researchers have shown that the inclusion of one more controller with a PID controller, such as a fuzzy logic controller can improve the results as compared to the use of the PID controller alone. The objective of this research is to experiment on the PID and fuzzy logic controller hardware and compare the results with those obtained from the simulation. In addition to this, the objective also is to find out the type of controller that would be most efficient in terms of settling time and the overshoot. This paper presents the comparison of PID and fuzzy logic controller simulation and experimentation on the ha...
A completed case study on fuzzy logic control of thermal processes has been carried out using a professional laboratory oven for industrial purpose as an experimental test rig. It involved system engineering design analysis, control synthesis, and implementation as well as application software and signal interface design and development. The resulting expertise and lessons learned are reported in this contribution. The structure of PD type of fuzzy logic controllers is closely discussed along with synthesis issues of membership functions and knowledge rule base. Special software was developed using Microsoft Visual Studio, C++ and Visual basic for GUI for a standard PC platform. The application software designed and implemented has four modules: FIS editor, Rule Editor, Membership Function Editor and Fuzzy Controller with Rule Viewer. Quality and performance of the overall fuzzy process control system have been investigated and validated to fulfill the required quality specifications.
Fuzzy logic technique is an innovative technology used in designing solutions for multi-parameter and non-linear control models for the definition of a control strategy. As a result, it delivers solutions faster than the conventional control design techniques. This paper thus presents a fuzzy logic basedtemperature control system, which consists of a microcontroller, temperature sensor, and operational amplifier, Analogue to Digital Converter, display interface circuit and output interface circuit. It contains a design approach that uses fuzzy logic technique to achieve a controlled temperature output function.
The paper proposes the realization of a Fuzzy Logic Temperature Controller. In this paper an analysis of Fuzzy Logic Controller is made and a temperature controller using MATLAB is developed. Here we used Fuzzy Logic Toolbox which is very useful software for development and testing of Fuzzy Logic system. It can be very quickly implemented and its visual impact is very encouraging. In this controller the Rule Base, membership functions and inference engine are developed either using digital systems such as memory and logic circuit or it can be developed using analog CMOS circuits. Analog Fuzzy systems are popular because of their continuous-time-processing and high frequency and low power implementation.
2021
Today’s need becomes compulsion to make the invention in the various control system due to the continuous and regular changing in technology and industrial processes. Control system requires fast and flexible responses. The its design need to provide easy and handy practical solution so that it accomplishes the performance requirement. From last few decades, we see emerging and innovative techniques of intelligent control are in the development stage and also developed. One of the areas of soft computing is Fuzzy logic (FL). FL is a intelligent control ability. Its knowledge based operational rules is useful for implementation with ease to control a complex system. In this article, a simple fuzzy controller structure is proposed. Generally we require information on the derivation of the controlled system output variable. But proposed system does not require. Getting the data of output derivation is not so easy and it’s cost more. In this paper a fuzzy logic controller (FLC) is devel...
2009
This work presents a new approach for controlling dynamic parameters of thermal power plant using Fuzzy logic. The control strategy is based on supervisor level using Fuzzy logic that is required to determine automatically the optimal process set points of regulations level. A thermal power plant simulator has been developed through the use of Matlab-Simulink. Besides, this paper describes hardware implementation using PLC based DCS.
SpringerPlus, 2016
Background With advances in power electronics and microprocessors, power electronics technology has widely used for many applications. Nowadays, AC/DC converters, which are also known as rectifiers, are used in adjustable speed drives, uninterruptible power supply systems, photovoltaic systems, battery energy storage systems, DC motor drives and communication systems (Singh et al. 2004; Blasko and Kaura 1997). AC to DC conversion has been performed by an uncontrollable diode rectifier or a phase controlled thyristor rectifier. Although these rectifiers have high reliability, simple structure and low cost, they have many disadvantages such as low power factor, high THD and unidirectional power flow. Moreover, these rectifiers that produce high harmonic currents are actually a harmonic source and have caused harmonic problems (Dannehl et al. 2009; Sekkeli et al. 2015). To solve these problems, new standards have been introduction by a number of countries and international organizations to limit harmonics formed in the current drawn from main supply by rectifiers. During the past 20 years, the interest in AC/DC rectifiers has been growing by day by due to the increasing concern about the harmonic pollution in the power systems. Thanks to the rapid development of technology, new rectifier type for
The heating system is widely used because it can sustain wide range of temperature. So temperature control is of prime importance. The heating systems are used for controlled maintenance of indoor ambient characteristics in optimal manner. The objective of these systems is to achieve comfortable and pleasant sensation of people staying in the warm area. The heating control problem is tackled by a fuzzy control scheme. Fuzzy logic systems are employed to maintain the room temperature in required range by determines the maximum and minimum for temperature. One important Artificial Intelligence tool for automatic control is the use of fuzzy logic controllers, which are fuzzy rule-based systems comprising expert knowledge in form of linguistic rules. These rules are usually constructed by an expert in the field of interest who can link the facts with the conclusions. Fuzzy Logic is a paradigm for an alternative design methodology, which can be applied in developing both linear and non-linear systems for embedded control. By using fuzzy logic, designers can realize lower development costs, superior features and better end product performance. In control systems there are a number of generic systems and methods which are encountered in all areas of industry and technology. From the dozens of ways to control any system, it turns out that fuzzy is often the very best way. The only reasons are faster and cheaper. One of successful application that used fuzzy control is heating control system. This paper describes the concept of using simulation as a tool for performance validation and energy analysis of heating systems.
Fuzzy Inference System - Theory and Applications, 2012
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