Level Control in Horizontal Tank by Fuzzy-PID Cascade Controller (original) (raw)
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IJERT-Water Tank Level Control System using Self-Adaptive Fuzzy-PID Control
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/water-tank-level-control-system-using-self-adaptive-fuzzy-pid-control https://www.ijert.org/research/water-tank-level-control-system-using-self-adaptive-fuzzy-pid-control-IJERTV3IS061601.pdf This paper demonstrates the performance of self-adaptive fuzzy-PID controller to control level of an automatic water level control system. The traditional PID controller cannot give satisfactory response to liquid level systems, because there exists time delay in this type of systems. Therefore, a self-adaptive fuzzy control is developed by combining the advantages of fuzzy and PID controller is applied to water level systems. In this paper, mathematical model for a first order tank system with valve lag, measurement lag and time delay are considered. For the water tank level control system (WTLCS), the measurements are carried out from process plant which is located at process dynamics and control laboratory, VIT University. The performance analysis of the self-adaptive fuzzy-PID controller and conventional PID controller has been implemented in MATLAB and Simulink for the first order WTLCS. The comparison of various time domain parameters is performed to prove that the self-adaptive fuzzy-PID control is superior to conventional controllers.
Level Control of Two Conical Tank Non Interacting System using PID and Fuzzy Logic
IJIREEICE, 2017
Non-linear process control is a difficult problem in process industries. Conical tank level control is one among them. Conical tanks are widely used in many industries due to its shape which provides easy discharge of water when compared to other tanks. Moreover, liquid level control of a conical tank is still challenging for typical process control because of its nonlinearities by a reason of constantly changing cross section area. By using fuzzy logic, designers can realize lower development costs, superior features, and better end product performance. Fuzzy is often the very best way as they are faster and cheaper. One of successful application that used fuzzy control is liquid tank level control. The purpose of this project is to design a simulation system of fuzzy logic controller for liquid tank level control by using simulation package which is Fuzzy Logic Toolbox and Simulink in MATLAB software. In this paper the mathematical modeling of two non-interacting conical tanks by PID controller and fuzzy. In this paper, we take the liquid level water tank, and use MATLAB to design a Fuzzy Control. Then we analyze the control effect and compare it with the effect of PID controller. As a result of comparing, Fuzzy Control is superior to PID control. Especially it can give more attention to various parameters, such as the time of response, the error of steadying and overshoot. Comparison of the control results from these two systems indicated that the fuzzy logic controller significantly reduced overshoot and steady state error.
Stabilization of liquid level in a tank system based on fuzzy logic controller
IAES International Journal of Robotics and Automation (IJRA)
Process industry needed a fast executed automatic control system capable of handling uncertain, vague problems and nonlinear control variables. Liquid level control is one of the emerging control problems getting the interest of technical experts in the area of control. This paper is based on a fuzzy logic control strategy to maintain and stabilize the liquid level in a tank system that deals with pumping of liquid in tanks as well as regulating liquid level and pushing off the liquid into another tank. Fuzzy controller attains optimum performance by eliminating perturbation in steady state and vanishing the overshoot as compared to proportional, integral, and derivative (PID) controller. The proposed fuzzy logic controller shows minimal steady error as compared to PID controller. The defuzzification of the proposed scheme is based on the centroid method to obtain optimum results. The settling time is nearly 50 second while using fuzzy logic control as compared to 80 seconds in PID ...
Level Control of Tank System Using PID Controller-A Review
This paper discusses the review of level control of tank system using PID controller. PID controller use for one or more tank system. PID has fast response. Paper present different methods of level control. Eliminate the steady state error. It is most common way of solving problems of practical control systems.
An Intelligent Controller of Nonlinear Conical Tank Water Level System
The Academic Research Community Publication, 2018
The present research presents an intelligent fuzzy logic controller (FLC) system for control water level of nonlinear systems, whereas the cross-section area of the vertical water is not constant (conical tank). The mathematical model of the conical tank level system was derived and its simulation runs were carried out by considering the FLC. For comparative analysis, a similar test runs were also carried out by means of conventional ZN based PI-mode. Interestingly, the results illustrate that applying the FLC system in the control loop in the conical tank system could provide a good tracking performance than that of conventional PI model.
Liquid Level Control of Coupled-Tank System Using Fuzzy-Pid Controller
International journal of engineering research and technology, 2017
Liquid level control of coupled-tank is widely used in the chemical industry-the environment is often affected by noise. The article deals with the fuzzy-PID controller applied to the nonlinear dynamic model of the liquid level of the coupledtank system, taking into account the effects of noise. Fuzzy-PID controller is designed based on PID initial parameters (determined based on the linear model) and fuzzy logic calculator for tunning PID parameters (suitable for nonlinear models and noise). The study results are caried out throught simulation model on Matlab using the coupled-tank nonlinear model with noise, applying the fuzzy-PID proposed controller, PID based on Ziegler Nichols.
Design of a Fuzzy Logic Based Controller for Fluid Level Application
World Journal of Engineering and Technology, 2016
In industrial process control, fluid level control is one of the most basic aspects. Many control methods such as on-off, linear and PID (Proportional Integral Derivative) were developed time by time and used for precise controlling of fluid level. Due to flaws of PID controller in non-linear type processes such as inertial lag, time delay and time varying etc., there is a need of alternative design methodology that can be applied in both linear and non-linear systems and it can be execute with fuzzy concept. By using fuzzy logic, designer can realize lower development cost, superior feature and better end product. In this paper, level of fluid in tank is control by using fuzzy logic concept. For this purpose, a simulation system of fuzzy logic controller for fluid level control is designed using simulation packages of MATLAB software such as Fuzzy Logic Toolbox and Simulink. The designed fuzzy logic controller first takes information about inflow and outflow of fluid in tank than m...
2015
In modern industrial control systems, the liquid level is one of the important factors as the control action for level control in tanks containing different chemicals or mixtures of liquids is concern. From the various controllers available one would find it difficult to identify the most appropriate one for excellent performance. Comparative studies of the performances of the conventional PID, Fuzzy PID and Neural PID controllers on systems of tanks are conducted in this work. The simulation results show that Fuzzy PID has smaller settling time in single, four and five tank while conventional PID has smaller settling time in couple and three tank control system.
Implementation of Fuzzy-PID Controller to Liquid Level System using LabVIEW
The paper describes about the liquid level control system which is commonly used in many process control applications. The output of the level process is non-linear and it is converted into the linear form by using Taylor Series method. The aim of the process is to keep the liquid level in the tank at the desired value. The conventional proportional-integral-derivative (PID) controller is simple, reliable and eliminates the steady state error. Fuzzy logic controllers are rule based systems which are logical model of the human behavior of the process. The fuzzy controller is combined with the PID controller and then applied to the tank level control system. This paper compares the transient response as well as error indices of PID, fuzzy, fuzzy-PID controllers. The responses of the fuzzy-PID controller are verified through simulation. From the simulation results, it is observed that fuzzy-PID controller gives the superior performance than the other controllers. The absolute error of fuzzy-PID controller is 56.6% less than PID controller and 55.6% less than the fuzzy controller. The LabVIEW software is used to simulate the system. The simulated results validate the method implemented here.
A Robust Fuzzy Logic Control of Two Tanks Liquid Level Process
— An attempt has been made in this paper to analyze the efficiency of Fuzzy Logic, PID controllers on Non Interacting Two Tanks (Cylindrical) Liquid Level Process. The liquid level process exhibits Nonlinear square root law flow characteristics. The control problem formulated as level in second tank is controlled variable and the inlet flow to the first tank is manipulated variable. The PID Controller is designed based on Internal Model Control (IMC) Method. The Artificial Intelligent Fuzzy logic controller is designed based on six rules with Gaussian and triangular fuzzy sets. MATLAB-Simulink has been used to simulate and verified the mathematical model of the controller. Simulation Results show that the proposed Fuzzy Logic Controller show robust performance with faster response and no overshoot, where as the conventional PID Controller shows oscillations responses for set point changes. Thus, the Artificial Intelligent FLC is founded to give superior performance for a Non linear problem like two tanks. This paper will help the method suitable for research findings concerning on two tank liquid level system. Keywords—Fuzzy Logic Controller, MATLAB– Simulink, PID and Two tank Non-interacting level system.