Experimental Validation of IMC-PID-FOF Controllers on the Water Level Tank System (original) (raw)
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Development of PID Controller for Controlling Desired Level of Coupled Tank System
The industrial application of Coupled Tank System (CTS) are widely used especially in chemical process industries. The overall process need liquids to be pumped, stored in the tank and pumped again to another tank for certain desired level. Nevertheless, the level of liquid in tank need to be controlled and flow between two tanks must be regulated. This paper presents development of Proportional-Integral-Derivative (PID) controller for controlling the desired liquid level of the CTS. Various conventional techniques of PID tuning method will be tested in order to obtain the PID controller parameters. Simulation is conducted within MATLAB environment to verify the performances of the system in terms of Rise Time (Ts), Settling Time (Ts), Steady State Error (SSE) and Overshoot (OS). Four techniques which are trial and error method, auto-tuning method, Ziegler-Nichols (Z-N) method and Cohen-Coon (C-C) method will be implemented and all the performance results will be analyzed. It has been demonstrated that performances of CTS can be improved with appropriate technique of PID tuning methods.
Two Degree of Freedom PID Controller for Quadruple Tank System
2015
This work presents an overview of designing and tuning of 2 DOF PI and PID controller for single and two tank interacting as well as non-interacting system. Transfer function of the plant i.e. single tank system and two tank non-interacting as well as interacting system calculated practically, following a mathematical model approach. Conventional PI and PID controller has a limitation when it is tested for set point tracking along with disturbance rejection. We can get a good set point tracking response and good disturbance rejection response separately but difficult to get simultaneously.2 DOF PI and PID controller overcome this disadvantage; it simultaneously provides a good set point tracking as well as good disturbance rejection response. Controller parameters calculated through the Ziegler Nichols’ open loop method. Controller action tested practically on the quadruple tank system using National Instruments’ LabVIEW and compared with the simulation results. Set point and trends...
Comparison for Level Control of a Coupled-Tank using PI, PI-plus-Feedforward, and IMC Controllers
International Journal of Scientific and Research Publications (IJSRP), 2018
This paper investigates the performance of various control schemes for level control of a coupled tank process. The nonlinear dynamic model of the system was derived using the analytical and empirical approaches. To investigate the performance of the controllers, proportional plus integral control, proportional plus integral plus feedforward control and internal model control (IMC) have been proposed. The PI gains were determined using pole placement, Ciancone correlation, and Cohen-Coon tuning techniques. Time response specification and mean absolute error (MAE) are used to assess the level control performance of the designed controllers. Comparative MATLAB simulation assessments have shown that IMC with the least MAE value and fastest settling time has the best tracking performance as compared to other controllers.
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 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.
Control of a Two Layered Coupled Tank: Application of IMC, IMC-PI and Pole-Placement PI Controllers
International Journal of Multidisciplinary Sciences and Engineering (ISSN 2045-7057), 2013
Proportional Integral Derivative (PID) controller remains the most widely and applicable type of controller used for process control applications in industries till date. However the efficacy of this controller lies in the tuning technique used in the determining its parameters. In this paper, we adopt a two layer coupled tank system whose transfer function was obtained via mathematical modeling. Thereafter the comparison of the performance of the PID controller based on two different tuning techniques – pole placement and internal model control (IMC) technique and that of another controller – the IMC controller was made. This is aimed at determining which tuning technique and control strategy produces a better performance on the basis of the transient response and Integral Absolute Error (IAE) for the system. The design and simulation is being carried out using the MatLab/ Simulink Toolbox and the simulation results shows that the IMC and IMC-tuned PI controller has an improved performance over the Pole-Placement-PI controller.
2014 Ieee International Conference on Advanced Communications Control and Computing Technologies, 2014
A multi tank level control system includes both the example of interacting and non-interacting system. In this system, we have considered three tanks each having equal area and each tank can be assumed as a first order system which are connected in interacting and non-interacting mode. The control system is intended to maintain the level of the third tank at some predefined value irrespective of changes of inflow of first tank. Conventional PID controller is a powerful controller used in process industries to regulate and control process variables. In this paper, we also consider the effect of the disturbance on the response of the system. According to these disturbances, we need to implement feed forward controller with better tuning algorithm. Thus, we implement transfer function of above system and behaviour is observed with step input.
The Coupled-Tank (CT) system remains an important tool for research by process control engineers. In this paper, we have addressed the issue of performance analysis of three control schemes, PI (based on pole placement, ZN and Ciancone correlation tuning methods), PI-plus-feedforward and MPC which have not been done in the present literatures. However, effective control of a system depends largely on the accuracy of the mathematical model that predicts its dynamic behaviour. The nonlinear model for the CT system based on analytical technique has been obtained. Linear models for the CT system were obtained based on analytical and empirical techniques. Accuracy of the linear models was investigated based on Final prediction error, Mean-square error, Integral absolute error, Mean absolute error and Confidence level. Empirical model was found to be more accurate and indeed processes are associated with Deadtime naturally. Proportional Integral (PI) control systems based on Ziegler Nichols (ZN), Ciancone Correlation (CC) and Pole Placement (PP) tuning methods were designed for liquid level control in the CT system tank 2. Integral absolute error and Integral square error results showed that PI controller did not meet all the specified control objectives. To improve the response, a feedforward controller was incorporated to the PI controller and the response was compared to that of a Model Predictive Controller (MPC). Simulations results showed that both PI-plus-feedforward and MPC satisfied all control specifications. However, MPC response was more satisfactory in terms of disturbance handling and time response criteria.
Journal of Robotics and Automation
The Coupled-Tank (CT) system has wide applications in process industries such as petrochemical , waste water treatment and purification, biochemical, spray coating, beverages and pharmaceutical industries. A typical process control representative is the CT liquid level control problem [1]. Controlling the liquid level in a precise manner has been an essential task in the process industries. Usually, liquids are pumped to the tanks, stored in tanks for further process operations and flow through the coupled-tanks [2]. The CT level control has been an interesting area of research and many control strategies have been proposed.
Journal of Physics: Conference Series, 2019
This work presents the analysis and design of a generalized proportional integral control strategy for a level control in a coupled tank system, such analysis is made under the active disturbance rejection. The principle objective is to show the advantages of the control strategy generalized proportional integral as to signals tracking and disturbance rejection, compared to conventional control techniques such as the proportional integral derivative control. To validate the process, the modeling of the system was carried out and with this model simulations were carried out under nominal conditions, applying the two control strategies. It was found that the generalized proportional integral control presented a better performance since it achieves a lower mean squared error percentage than the proportional integral derivative control, even in the presence of disturbances.