Modelling and Simulation of Non Linear Tank (original) (raw)
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Level Control of Non Linear Tank ProcessUsing Different C ontrol Technique
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2014
PID controller plays very important role in many process control industries. In this paper Ziegler- Nichols controller, Tyreus and Luyben controller, Cohen Coon controller are used to control the level of the conical tank. The controller is designed based on the mathematical model of the system. Non-linear variation is exigent in conical tank because of some of the awkwardness compared to linear system based on analysis, non-linear system is preferred by number of industries. For disposal of solid material non-linear is the system will be best supporter for controller used for conical tank. In this work, a non linear tank process is identified as first order plus dead time model and identified model is used for controller implementation. The closed loop response of process system is obtained using MATLAB simulink. Based upon obtained results and time domain specifications best tuning PID controller parameter is highlighted.
Controller Tuning Method for Non-Linear Conical Tank System
In this paper, we propose a new technique for implementing optimum controller for a conical tank. The objective of the controller is to maintain the level inside the process tank in a desired value. Hence an attempt is made in this paper as Internal Model Based PID controller design for conical tank level control. For each stable operating point, a first order process model was identified using process reaction curve method. The real time implementation is done in Simulink using MATLAB. The experimental results shows that proposed control scheme have good set point tracking and disturbance rejection capability.
Design of Model based controller for Two Conical Tank Interacting Level systems
IJMER
This paper presents the modelling and control of Two Tank Conical Interacting systems which is highly a non linear process. A Model based controller is designed for the process at different operating regions and its performance is studied with and without disturbance. The aim is to control the liquid level of tank. Piecewise linearization technique is applied for linearising the non linear system output. An Internal Model control is designed for each region. The controller will be simulated using MATLAB SIMULINK software.
MODELLING AND APPLICATION OF A COMPUTER-CONTROLLED LIQUID LEVEL TANK SYSTEM
Liquid level tanks are employed in many industrial and chemical areas. Their level must be keep a defined point or between maximum-minimum points depending on changing of inlet and outlet liquid quantities. In order to overcome the problem, many level control methods have been developed. In the paper, it was aimed that obtain a mathematical model of an installed liquid level tank system. Then, the mathematical model was derived from the installed system depending on the sizes of the liquid level tank. According to some proportional-integral-derivative (PID) parameters, the model was simulated by using MATLAB/Simulink program. After that, data of the liquid level tank were taken into a computer by employing data acquisition cards (DAQs). Lastly, the computer-controlled liquid level control was successfully practiced through a written computer program embedded into a PID algorithm used the PID parameters obtained from the simulations into Advantech VisiDAQ software.
Comparative Analysis of Different Controller for a Nonlinear Level Control Process
Controlling the level in the nonlinear process is hectic because of its shape. In many industries the flow and level control plays a vital role. Controlling the level in the conical tank is a challenging process because of its nonlinearity and constantly changing of cross section with respect to height. The Model for a conical tank was identified for different operating regions which were best approximated to first order plus dead time model. For the identified model different controllers such as Direct Synthesis Proportional Integral (DSPI) and Model Predictive Control (MPC) were designed and compared.
Soft Computing Technique and Conventional Controller for Conical Tank Level Control
Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 2016
In many process industries the control of liquid level is mandatory. But the control of nonlinear process is difficult. Many process industries use conical tanks because of its non linear shape contributes better drainage for solid mixtures, slurries and viscous liquids. So, control of conical tank level is a challenging task due to its non-linearity and continually varying cross-section. This is due to relationship between controlled variable level and manipulated variable flow rate, which has a square root relationship. The main objective is to execute the suitable controller for conical tank system to maintain the desired level. System identification of the non-linear process is done using black box modelling and found to be first order plus dead time (FOPDT) model. In this paper it is proposed to obtain the mathematical modelling of a conical tank system and to study the system using block diagram after that soft computing technique like fuzzy and conventional controller is also used for the comparison.
Design and Performance Analysis of Level Control Strategies in a Nonlinear Spherical Tank
Processes
This work seeks to contribute to the study of techniques for level control considering a nonlinear plant model. To achieve this goal, different approaches are applied to classical control techniques and their results are analyzed. Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Model Predictive Control (MPC) and Nonlinear Auto-Regressive Moving Average (NARMA-L2) controllers are designed for the level control of a spherical tank. Subsequently, several tests and scenarios similar to those present in industrial processes are established, while the transient response of the controllers, their performance indices for monitoring the reference value, the rejection of disturbances, the presence of parameter uncertainties and the effects of noise are analyzed. The results show good reference tracking, with a settling time of approximately 5 s for 5 cm and a rise time of less than 4 s. No evidence for steady-state error or overshoot ...
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.
International Journal of Computer Applications, 2013
Control of nonlinear process is a complicated task in industrial environment. In this work, adaptive control technique is discussed in control of single conical tank level control system is a nonlinear system is identified mathematically. Analytical modeling were implemented and simulated in MATLAB SIMULINK and transfer function isobtain from the simulated response and PI controller parameter were derived for implementing gain scheduling adaptive controller and synthesis based method is used to obtain PI parameters for multiple linear models. The simulation studies were carried out for two controller parameters. From the results based on Performance indices like Integral Squared Error (ISE), it is proved the controller implemented using gain scheduling adaptive control technique out performs well over synthesis method based tuned multi PI controller.
Level Control of Coupled Conical Tank System using Adaptive Model Predictive Controller
IEEE, 2021
The controlling techniques of liquid level in a coupled conical tank system is a challenging task owing to its continuous changing cross-section and non-linearity in the system. In this paper, an adaptive model predictive controller (AMPC) is presented to control the valve speed of conical shaped tank to maintain the liquid level. In AMPC, the plant model states are changed in every cycle along with the MPC controller to update the plant parameters in a precise manner, which is a major concern due to its non-linear behavior. Moreover, the comparative analysis of coupled conical tank system with other controllers like Fractional order PID (FOPID) controller and PID controller is carried out. The simulation results represent the superiority of the AMPC controller as compared to the other controlling methods in terms of response time and overshoot.