Optimized Tuning of PI Controller for a Spherical Tank Level System Using New Modified Repetitive Control Strategy (original) (raw)
Related papers
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.
Control Of Non Linear Spherical Tank Process With PI-PID Controllers – A Review
This paper focuses on the review of control methods for spherical tank system and tuning of non-linear PI / PID controllers in real time. The control of liquid level in spherical tank is complicated with conventional controllers due to variation in the area of transverse section of the tank. Thus the proposed non-linear PI and PID controllers are simulated and compared with the conventional PI and PID controllers available in the literature for spherical tank system. The proposed controllers are tuned based on Cohen Coon tuning method from the open loop response of the experimental setup of spherical tank in real time. The results of the proposed control methods are presented and compared with the conventional PI and PID controllers. The performance of the proposed control methods are evaluated with time domain specifications. The proposed non-linear PI and PID controller provides better response than the conventional PI and PID controllers for the spherical tank system.
A New Approach of Control Strategy for a Spherical Tank Level Process
2015
The control of spherical tank level process is complex because of its dynamics are highly nonlinear and time varying with change in gain of several orders. Hence in this work, modeling and control of spherical tank level process is considered. The mathematical model of spherical tank level process is developed and a fuzzy clustering based control system is proposed for a spherical tank level process. The dynamics of the process are derived from the differential equation and worst case model parameters are identified by influencing the step test technique. Here Recursive Least Squares (RLS) fitting method is also adapted to yield the optimized PI controller parameters. The simulation results are furnished to illustrate the effectiveness of proposed controller.
Non Linear Spherical Tank Control Using IMC Tuning Method
Controlling the nonlinear tank is very difficult. Because nonlinear tank have variation in area of cross section. The aim of this paper is to implement optimum controller for a spherical tank. The objective of the controller is to maintain the level inside the process tank in a desired value. The real time implementation of the process is designed and implemented in MATLAB using data acquisition module. The identified mathematical model is in the form of first order plus delay time process (FOPDT).[1] The controller design is compared with different controller tuning methods. The best controlling methods is determined based on no overshoot, better set point tracking, faster settling time and lower performance indices.[1].
Optimization of pi controller for level control of water tank system
2020
Alhamdulillah. All praises to Allah for His all blessing in completing this master project. First and foremost, I would like to express my special appreciation to my supervisor, Ir. Dr. Shafishuhaza Sahlan, for her continuous supervision and guidance to help me throughout this master project journey. Not forgotten, my appreciation goes to all lecturers who have taught me throughout the master"s program. Sincere thanks to all my friends especially my classmates for their kindness and moral support during my study. Thanks for the friendship and memories. My gratitude also goes to my beloved family. Thanks for unconditional love and encouragement. Thank you very much.
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 ...
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.
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.
Design PI Controller for Tank Level in Industrial Process
Iraqi Journal for Electrical and Electronic Engineering, 2022
In today’s chemical, refinery, and petrochemical sectors, separation tanks are one of the most significant separating processes. One or more separation tanks must operate consistently and reliably for multiple facilities’ safe and efficient operation. Therefore, in this paper, a PI controller unit has been designed to improve the performance of the tank level controller of the industrial process in Basrah Refinery Station. The overall system mathematical model has been derived and simulated by MATLAB to evaluate the performance. Further, to improve the performance of the tank level controller, optimal PI parameters should be calculated, which Closed-Loop PID Autotuner has been used for this task. Several experiments have been conducted to evaluate the performance of the proposed system. The results indicated that the PI controller based on the Autotuner Method is superior to the conventional PI controller in terms of ease to implement and configuration also less time to get optimal ...
Simple tuned adaptive PI controller for conical tank process
This paper proposes an idea for designing a continuously tuned adaptive PI controller for a non-linear process such as conical tank. In this paper, a simple tuning system is used to continuously tune the controller parameters in correspondence with the change in operating points. For each stable operating point, a FOPTD model was identified using process reaction curve method. The estimated model parameters are used to calculate the controller parameters for each operating points. Based on these calculated controller parameters and its operating points, a tuning system was created. The tuning system will able to interpolate and extrapolate the relation between control variable and the controller parameters over entire span of control variables. Finally, a detailed time-domain modeling of the conical tank was performed. Then the adaptive PI controller was implemented in Matlab and was simulated to verify its performance. Thus the adaptive controller was able to produce a consistent response regardless of parametric variations with minimum overshoots and minimum settling time.