Development of fuzzy logic water bath temperature controller using MATLAB (original) (raw)
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Realization of Fuzzy Logic Temperature Controller
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.
Water Temperature Controller Using Microcontroller And Correction Using Fuzzy Logic
2014
— Many people of our country is involve in fishery, but different fish live in different temperature and pressure if the temperature vary the fish may be die, so the temperature must maintain within certain range but it is very difficult for them to maintain the temperature and pressure, if they try to maintain all the parameter the cost also higher, so we must think a alternate process which is our desire project. In this project we basically control the water temperature using microcontroller PIC18F4520.We first measure the water temperature of the water and then display it in the seven segment display now if the temperature is higher then on the cooler and if the temperature is lower then on the hot air fan. We also use fuzzy controller to control the water temperature and pressure perfectly. To program the microcontroller we first write the program in C-language, and then we convert the code in the hexadecimal code and burn the code within the chip and configure the microcontrol...
Application of Fuzzy Logic Temperature Controller for Water Bottle Industry
Computer Engineering and Intelligent Systems
The mathematical modeling involves convectional controller which affect the performance non-Linear and complex control system of the Bottle water industry. The system instability can be overcome by using intelligent controller to control and Monitor water temperature within a specific period of time in order to avoid overshoot and absolute error, with better temperature tracking capability. However, most industry does not have accurate and reliable monitoring mechanism capable of sensing when the water Temperature increases. The fuzzy Logic is used to control the Temperature of Bottle water at difference time of operation. This operational failure can be overcome by designing a model that will monitor and control the water temperature process thereby improving temperature control in water bottle industry using Fuzzy Logic Controller. MATLAB Software was used to carry out simulations to develop Temperature control in Bottle water industry with aims of improving operational mechanism of the industry. This model can then be trained with result gotten from the mathematical model in order to monitor and control the Water Temperature. The result showed that Bottle water Temperature with and without Fuzzy Logic Controller were 85 0 C and 65 0 C respectively. The Temperature increased by 20 0C. With these results, it shows that using fuzzy Logic Controller gives a better result than when fuzzy logic is not used.
Fuzzy Logic Controller for Boiler Temperature Control using LabVIEW and Matlab
International Journal of Control and Automation, 2016
The aim of this project is to achieve a precise temperature control of boiler and it can be done by fuzzy logic controller. Fuzzy logic controller is computer generated and is easy to implement. Fuzzy logic controller being more efficient than other conventional controllers provide us with better and accurate results. MatLab simulation and Labview experimental results clearly show the amount of overshoot and settling time are modest, it also makes the boiler cost effective by achieving the target temperature in less time.
Industrial Water Bath Temperature Control System using MATLAB Environment
2013
Artificial Neural Network is an effective tool for highly nonlinear system. With the advent of high-speed computer system, there is more increased interest in the study of nonlinear system. Neuro control algorithm is mostly implemented for the application to robotic systems and also some development has occurred in process control systems. Process Control systems are often nonlinear and difficult to control accurately. Their dynamic models are more difficult to derive than those used in aerospace or robotic control, and they tend to change in an unpredictable way. This paper gives an example where a multilayered feed forward back propagation neural network is trained offline to perform as a controller for a temperature control system with no a priori knowledge regarding its dynamics. The inverse dynamics model is developed by applying a variety of input vectors to the neural network. The performance of neural network based on these input vectors is observed by configuring it directl...
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/design-of-genetic-fuzzy-logic-based-hybrid-temperature-controller-and-comparison-with-other-controllers https://www.ijert.org/research/design-of-genetic-fuzzy-logic-based-hybrid-temperature-controller-and-comparison-with-other-controllers-IJERTV3IS20453.pdf Water bath systems are nonlinear in behaviour thus conventional controllers like P, PI, PID are not so efficient. The Fuzzy Logic Controller has found better than PID in temperature control of water bath system in literature because the FLC processes user-defined rules governing the system, it can be modified easily to add, improve or alter system performance. This work presents Genetic Algorithm for the optimization of Fuzzy Logic Controller rule base for the temperature control of water bath system with goal of Zero response error. MATLAB is used for the simulation with Genetic Algorithm toolbox. Simulation results show that performance of Fuzzy Controller improves when optimized by Genetic Algorithm. A comparison has been made among controllers studied.
FUZZY BASED CONTROL USING LabVIEW FOR MISO TEMPERATURE PROCESS
IJRET, 2012
This project aims at designing and implementing a fuzzy controller for Multiple Input Single Output temperature process. Temperature control of water in the tank is achieved by varying current to the heating rod and inlet flow rate by a fuzzy controller. The system consists of a tank, reservoir, variable speed pump, temperature sensor placed inside a heating tank containing the heating rod, voltage controlled current source and computer. Water is pumped into the tank from reservoir and RTD measures the current temperature. The signal from the temperature sensor is sent to the DAQ interfaced to the computer. LabVIEW software is used to acquire the input signal and send the output signal that is determined by the control algorithm. Fuzzy logic controller is designed in LabVIEW. Based on the set point temperature, the controller sets the appropriate current to the heating rod. If the required temperature is less than that sensed by the temperature sensor, the flow rate of water into the tank is controlled by a variable speed pump. While conventional controllers are analytically described by a set of equations, the FLC is described by a knowledge-based algorithm. Thus this system is highly efficient in both heating and reducing the temperature of the tank. A fuzzy logic controller gives faster response, is more reliable and recovers quickly from system upsets. It also works well to uncertainties in the process variables and it does not require mathematical modelling.
Temperature Control System Using Fuzzy Logic Technique
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.
MATLAB Interfacing: Real-time Implementation of a Fuzzy Logic Controller
IFAC Proceedings Volumes, 2013
In this work, the design and evaluation of a fuzzy logic control of liquid flow process is analyzed experimentally using MATLAB package. MATLAB is a widely used software environment for research and teaching applications on control and automation. The interface is a collection of hardware and software modules used to flexibly connect a plant, process or instrument (etc.) to a digital computer. The experimental performance of proposed fuzzy logic control is carried out on existing computer control of flow process. The program of Real-time data acquisition and control has been developed using modules called, "To Instrument" and "Query Instrument" of MATLAB for experimental work. Thus, The present implementation of intelligent fuzzy logic control on real-time basis is a pioneering work at laboratory scale. It is considered to be a great contribution in area of advanced process control systems. The simulation and experimental results clearly shows that the Intelligent Fuzzy Logic Controller gives a better control without overshoots of liquid flow rate in comparison with conventional PID controller.
Temperature Control using Fuzzy Logic
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 .