Coupled Tank Research Articles

Coupled Tanks Level Control Based on Volume Balance Method

Abstract The laboratory bench “Coupled tanks” represents a model of real technological plans where the levels and flow rates of liquids must be controlled. Such training benches are very common and there is a very large number of publications related to their control. All publications work with a non-linear model based on the Bernoulli equation for ideal fluids, which is non-linear – the square root of the fluid height is present. This equation or system of equations is linearized and attempts are made to control such systems by means of linear models. This article shows that this approach is not correct and proposes a completely different one based on the volume balance method.

Comparison of the Performance of Type-1 and Interval Type-2 Fuzzy PI Controllers for Liquid Level Control in a Coupled Tank System

In this study, liquid level control in a coupled tank system is realized with PI controllers whose parameters are adapted using fuzzy logic approximation methods. Type-1 fuzzy PI control, interval type-2 fuzzy PI control and classical PI+Feedforward control methods are applied to the tank system in real time for different reference liquid levels. The performances of the controllers are compared in terms of system response parameters such as rise time, settling time and overshoot percentage. In addition, the performance evaluation of the controllers over a certain period of time is also compared by calculating integral-based concepts that express error performance metrics such as integral square error (ISE), integral time square error (ITSE), integral absolute error (IAE) and integral time absolute error (ITAE). The obtained results show that the type-2 fuzzy PI controller shows the best performance, followed by type-1 fuzzy PI control and classical PI+FF controller, respectively.

Water Level Control in Coupled Tank System with PLC and IoT-Based PID Method

There are many advanced technological discoveries in industry, including the coupled tank. Coupled tanks are several tanks connected to each other. One of the quantities that is often controlled in the industry is the control of water levels. Water level control in a PLC and IoT-based coupled tank system is a medium for controlling and monitoring water levels remotely in real-time. The sensor used is a Differential Pressure Transmitter (DPT) with a pump motor actuator which is connected to an Omron PLC using an inverter. There is a disturbance in the form of setting the control valve opening. The control method used is the PID method with Ziegler-Nichols tuning and trial and error. Both methods analyzed which performance of the system response characteristics was better. It is proven that PID tuning is suitable for water level control of coupled tank systems.

Design of 3×3 Multi Input Multi Output (MIMO) Decoupling on Coupled Tank System with PID Controller

Multivariable processes are the general classification for process features in the chemical industry. The variables in a single process unit interact with one another through more than one input and output. Since parameters interact with one another, changing one parameter's variable requires changing another parameter's variable as well. Further research is needed to determine how to create controllers that can handle interactions in the process. A MIMO control system is exemplified by the coupled tank system. Coupled tanks are present, and they communicate with one another by horizontal pipes. An interacting system can be represented using a coupled tank setup. Decoupling can be added to reduce the interactions that take place between variables. According to the results of the simulation, adding decoupling reduces the IAE value compared to not adding it. When the setpoint for tank level 1 (H1) was changed, the system's IAE value was 17.35 without the addition of decoupling, whereas it was 11.71 with it.

Optimal tracking in two-degree-of-freedom control systems: Coupled tank system

This article presents an optimal design of a two-degree-of-freedom (2-DoF) controller that will lead to zero asymptotic steady-state tracking error. The reference inputs are chosen from the set of steps, ramps, and other persistent signals used currently. The main idea is to transform the tracking 2-DoF problem into an equivalent state-space feedback-control synthesis one. Where, an internal model of the reference input is introduced. Then, through the linear quadratic regulator (LQR) technique, the desired performance objectives are addressed by minimizing a quadratic cost function. Finally, the computed state-feedback optimal gains are linked to the polynomials used within the 2-DoF formalism. The fundamental aspect of the design is that it only utilizes the measurable information of the plant provided by its inputs and outputs and take advantage of efficient state-space numerical algorithms. The proposed method is applied to a coupled-tank system, the results achieved confirm the effectiveness of the approach.

ICT-Architecture design for a Remote Laboratory of Industrial Coupled Tanks System

ICT-Architecture design for a Remote Laboratory of Industrial Coupled Tanks System

Modified ant colony optimization based PID controller design for coupled tank system

Most of the optimization algorithm suffers from slow convergence and poor solution accuracy due to nonlinearity characteristics of the problem. This paper proposes a meta-heuristic method, namely the modified Ant Colony Optimization (m-ACO) technique to address these issues. The conventional ant colony optimization algorithm is improved by using multiple random initializations to increase the probability of getting a better start population and hence increase the possibility to achieve near-global optimum. The efficacy of the proposed algorithm is tested on classical benchmark functions and on the PID controllers. The performance of controllers depends on the selection of tuning parameters that are optimized to obtain an optimum solution. The m-ACO technique is used to optimize parameters of PID controller for Coupled Tank System. It is one of the benchmark control problems due to its nonlinear characteristics. The obtained results of the proposed algorithm are compared with the Zeigler Nichols tuned PID controller, and PSO tuned PID controller in terms of transient performances including rise-time, peak overshoot and performance parameters such as Integral Square Error (ISE) and Integral Absolute Error (IAE). The proposed method is also tested for showing effectiveness in set-point tracking and disturbance rejection.

Fractional Order Sliding Mode Controller for Coupled Tank System

In this paper, a fractional order sliding mode controller (FOSMC) is proposed for nonlinear coupled tank system. The proposed controller integrates the advantages of the fractional order control and sliding mode control. Fractional order controller has an extra flexibility to meet the specifications of the controller design and sliding mode control is a robust controller, which is able to respondtoexternal disturbances combined with nonlinear systems.The objective of the controller is to allow the system states to move to the sliding surface and remain on it so as to ensure the asymptotic stability of the closed-loop system. The stability analysis for the proposed controller is studied based on the Lyapunov stability theorem. Simulation results show the ability of the proposed controller to improve the system performance especially when the controlled system is exposed to external disturbances and variation of reference trajectory compared with the conventional proportional-integral-derivative controller (PID) and conventional sliding mode controller (SMC), which is based on integer order derivatives.

ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System

In this paper, a novel algorithm based machine learning technique for control nonlinear coupled tanks system is presented. An intelligent controller using adaptive neuro-fuzzy inference system (ANFIS) based reinforcement learning is proposed (ANFIS-RL) by representing the nonlinear coupled tanks system as a Markov decision process. A model-free learning algorithm has been used to train a policy that controls the liquid level of the tanks system without the need to determine the dynamic model of the controlled system. Based on the optimal learned policy, which is approximated by ANFIS, the controlled system can perform the best action quickly based on the states of the system. Simulation results demonstrated the feasibility of the proposed algorithm.

Tuning of the two degrees of freedom FOIMC based on the Smith predictor

This paper proposes a novel two degrees of freedom (2-DOF) fractional order internal model controller (FOIMC) for the height control of a coupled tank system. Coupled tank systems find applications in the process control industries. The level control of the coupled tank system is a challenging problem in the control systems because of its nonlinearity and time delay involved. The level control of the coupled tank system has variable servo tracking and disturbance rejection requirements. 2-DOF controller achieves better servo tracking and disturbance rejection than a one degree of freedom (1-DOF) controller. The proposed servo tracking controller is designed using the Bode’s ideal loop transfer function and direct synthesis approach. The parameters of the Servo tracking controller are tuned using peak overshoot and settling time specifications. The disturbance rejection controller is designed analytically. A detailed study of the effect of the fractional order on the disturbance rejection property and stability. Robust stability of the proposed controller is analysed using $$H_{\infty }$$ norm of the uncertainty bound. Comparison of the simulation results of the proposed controller with the state of the art showed better performance of the proposed controller. Frequency domain analysis also indicates the superior performance of the proposed 2-DOF FOIMC.

Design of decentralized controller for coupled tank system using BLT method

In this paper, controller design for multivariable coupled tank system is presented. The control of Coupled tank system offers difficulty due to interaction between the controlled variables. By considering the interaction, this paper describes the design of decentralized PI controller for coupled tank system using Biggest Log modulus Tuning method (BLT). The decentralized controllers are designed based on the fully coordinated design method by assuming controller parameters obtained by employing Ziegler-Nichol’s tuning method with proper design parameters. The design parameters are then adjusted to ascertain the stability of the system. The effectiveness of the designed controller is evaluated and the results interpreted by simulation using MATLAB SIMULINK software.

Feedback linearization and Backstepping controllers for Coupled Tanks

Feedback linearization and Backstepping controllers for Coupled Tanks

MODEL IDENTIFICATION AND LEVEL CONTROL OF COUPLED TANKS SYSTEM

The Couple Tank (CT) system remains as a benchmark to investigate and test new emerging control schemes in the process industry since its dynamic emulates many factual system in the field of process control. In this paper, we examine the performance evaluation of two control algorithms, proportional derivative controller (PD) and proportional-integral-derivative controller (PID). The dynamics of the CT system is experimentally derived by system identification method and validated with a mathematical model that depicts the dynamic behaviour of the coupled tank system. Furthermore, the control schemes are expanded on the model obtained through system identification method. The simulation results showed that the PD controller did not meet all the specified control objectives. To improve the response an integral controller was incorporated to the PD controller and the response was compared to that of the PID controller and uncompensated system. The results revealed that the PID controller satisfied all the control goals. However, the PD controller was more satisfactory in terms of time response criteria.

Model-based Dynamic Fractional-order Sliding Mode Controller Design for Performance Analysis and Control of a Coupled Tank Liquid-level System

In this paper, a model-based dynamic fractional-order sliding mode controller (FOSMC) is designed and implemented to a coupled tank experimental setup for controlling the liquid level. ...

Graphical Robust PID Tuning of TITO Processes

In this paper, PID controller for Decentralized TITO process is tuned using graphical approach. Ideal decoupler is used to decouple TITO system and then each decoupled system is approximated to FOPDT model. The Graphical method uses boundaries determined by the loci of stability and frequency domain characteristics such as Gain, and Phase margin etc. common region of these loci gives the values of the PID controller coefficients. The results are validated using MATLAB and the simulated results are presented for Coupled tank system.

RGA Based Decoupler Design for a Coupled Tank MIMO Process

The objective of this paper is to develop the Relative Gain Array (RGA) based Decoupler design with PI Controller for a MIMO Process. The contrsoller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of PI Controller with Decoupler scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for MIMO process that exhibits nonlinear behaviour.

LabVIEW Based Level Control of Coupled Tank System

This paper utilizes Variable Structure Control (VSC) to control the level of a two tank system. By using Sliding Mode Technique in VSC, the levels of the tanks are maintained at a desired setpoint. The system is subjected to the conventional PID controller and the results are brought out. To track the robustness of the system, an external disturbance is intentionally introduced. The ability of disturbance rejection is checked in both VSC and PID controllers. It is found that VSC offers quick settling time, low peak overshoot and low rise time, and as compared to PID control. LabVIEW(Laboratory Virtual Instrument Workbench) is the software used for the control of the whole process. This is very user friendly software. It uses Graphical programming technique. As an extension the control can be implemented by hardware using DAQ cards.

An Expanded Optimal Control Policy for a Coupled Tanks System with Random Disturbance

In this paper, an expanded optimal control policy is proposed to study the coupled tanks system, where the random disturbance is added into the system. Since the dynamics of the coupled tanks system can be formulated as a nonlinear system, determination of the optimal water level in the tanks is useful for the operation decision. On this point of view, the coupled tanks system dynamics is usually linearized to give the steady state operating height. In our approach, a model-based optimal control problem, which is adding with adjusted parameters, is considered to obtain the true operating height of the real coupled tanks system. During the computation procedure, the differences between the real plant and the model used are measured repeatedly, where the optimal solution of the model used is updated. On this basis, system optimization and parameter estimation are integrated. At the end of the iteration, the iterative solution approximates to the correct optimal solution of the original optimal control problem, in spite of model-reality differences. In conclusion, the efficiency of the approach proposed is shown.

An FO–[PI]λ controller for inverted decoupled two-input two-output coupled tank system

ABSTRACTIn this paper, a new structured fractional order-[proportional integral] () controller design method is demonstrated. The designed controller is implemented in decoupled Two-Input Two-Output (TITO) Coupled Tank System (CTS) for liquid level control. An inverted decoupling technique is used to decouple the TITO process into two independent SISO (single-input single-output) processes. The designed controller is implemented for each SISO process. A frequency domain approach is used to tune the parameters of the controller. While designing, to approximate the fractional integral terms of the controller, Oustaloup's Recursive Approximation (ORA) method is used in the stable frequency bands. To validate the proposed approach, the performance of the controller is compared with the existing controllers designed based on the same specifications. From the simulation and experimental studies, it is shown that proposed gives better performance than , PI and PID controllers.

Adaptive Control Scheme for Coupled Tank Process

The objective of this paper is to develop a Direct Model Reference Adaptive Control (DMRAC) algorithm for a MIMO process by extending the MIT rule adopted for a SISO system. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of adaptive techniques such as DMRAC control scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for multivariable process that exhibits nonlinear behaviour.