Synthesis of fuzzy sliding mode controller for liquid level control in spherical tank (original) (raw)

Fuzzy Logic Based PID Controller for a Non Linear Spherical Tank System

2014

Non-linear process control is a difficult task in process Industries. Spherical tank level control is one among them due to the variation in cross sectional area. In this project modeling of Spherical tank system is done. The implementation of fuzzy logic controller (FLC) and Fuzzy PID for a spherical tank to control liquid level is studied. System identification of spherical tank system is done which is identified to be non-linear. Here the conventional PID controller parameters are designed based on Ziegler-Nicholas tuning method. The process is designed and implemented in Mat lab. It is observed from the result that Fuzzy based PID controller perform well in terms of less settling time, rise time and no overshoot in process output.

Real Time Implementation of Fuzzy Based Adaptive PI Controller for a Spherical Tank System

International Journal of Simulation Systems Science & Technology, 2013

This paper proposes a new fuzzy adaptive variable digital PI controller for a single input single output non-linear spherical tank level process system. The open loop transfer function models are carried out at three different operating regions and those models are formulated based on the real laboratory scale system. The proposed FAPI controller is a combination of two input two output Fuzzy logic controller and a Variable digital PI controller. The input to the fuzzy controller is error and change in error and its outputs are K P and K I. The PI controller's parameters are estimated on-line based on error and change in error. The real time implementation and control of the process plant is done in MATLAB using VMAT-01 Data Acquisition Module. The objective is to make the output to settle fast with minimum overshoot and the disturbances do not affect the performances of the system.

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 ...

Investigation of Fuzzy Logic Controller for Conical Tank Process

The PID Controllers are commonly used in industries for nearly a century due to its simplicity, efficiency and flexibility. Recently, the control of non-linear processes in the industries have turned the attention towards the intelligent controllers such as, Neural Networks, Fuzzy Logic Controller, Genetic Algorithm tuned Controllers, Adaptive Controller, etc. This paper focuses on the Investigation of Intelligent Controllers for conical tank level process. A conical tank is a highly nonlinear process due to the variation in the area of cross section of the level system with change in shape. In this work, Fuzzy Logic Controller is designed for the control of nonlinear process to ensure the exact level maintenance. The simulation results are obtained by Servo and Regulator operation of the nonlinear conical tank process. For this work, Fuzzy Logic Controller is compared with Conventional PI Controller.

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.

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...

Designing of Fuzzy Logic Controller for Liquid Level Controlling

International Journal of u- and e-Service, Science and Technology, 2015

In control system there are a number of general systems and methods which are encountered in all areas of industry and technology. There are many ways to control any system, in which fuzzy is often the very best way. The only reason is faster and cheaper. One of successful application that is used for the controlling of liquid level is fuzzy logic controller. In order to find the best design to stabilize the liquid level in this method, some factors will be considered. For this paper, the liquid level was controlled by using three rules of membership function which then extended to five rules, seven rules and nine rules for verification purpose and further improvement of the system. This paper was focused to the software part only. By doing some modification in this paper, the design will be very useful for the system relates to liquid level control that widely use in industry nowadays. For a long time, the selection and definition of the parameters of PID controller are very difficult. There must be a bad effect if you do not choose nicely parameters. To strictly limit the overshoot, the use of Fuzzy controller can achieve a great control cause. In this paper, we take the liquid level water tank, and use MATLAB to design a Fuzzy Controller. Then we analyze the control effect and compare it with the effect of PID controller. As a result of comparing, Fuzzy Logic Controller is superior to PID controller. Comparison of the control results from these two systems indicated that the Fuzzy logic controller significantly reduced overshoot and steady state error.

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.

Fuzzy controller for adjustment of liquid level in the tank

This paper presents the fuzzy controller for adjustment of liquid level in the tank and presents the theoretical concepts of triangular fuzzy numbers mathematics. Using the fuzzy controller will be maintained constant the liquid level. The fuzzy controller was elaborated by authors in MatLab program and operation was simulated in SIMULINK program.

Real-Time Application of Sliding Mode Controller for Coupled Tank Liquid Level System

International Journal of Applied Mathematics, Electronics and Computers, 2016

In this paper, real time application of a sliding mode control (SMC) is used for level control of experimental setup of liquid level system due to its properties such as robustness against large parameter variation and disturbances rejection. A well-tuned conventional proportional integral (PI) controller is also applied to the two coupled tank system for comparison with the SMC controller. Experimentation of the coupled tank system is realized in two different configurations, namely configuration #1 and configuration #2 respectively. In configuration #1, the water level in the top tank is controlled by a pump. In configuration #2, the water level in the bottom tank is controlled by the water flow coming out of the top tank. The performance of controllers is analysed according to their tracking performance and error elimination capability for different references applied to the system. Experimental results prove that the SMC shows better trajectory tracking performance than PI controller in that the plant transient responses to the desired output changes have shorter settling time and smaller magnitude overshot/undershoot. Robustness of the SMC with respect to water level variation and capability to eliminate external disturbances are also achieved.