Liquid Level Tracking Control of Three-tank Systems

Yu, Shuyou; Lu, Xinghao; Zhou, Yu; Feng, Yangyang; Qu, Ting; Chen, Hong

doi:10.1007/s12555-018-0895-y

Cited by 15 publications

(4 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To establish a relationship between them, the 2nd time-derivative of h 2 is used which directly depends on the 1st time-derivativeḣ 1 of h 1 . According to (2) this directly depends on the control signal. By this relation it can be seen that the relative order of the control task is 2.…”

Section: Control Task Of the Dual Tank Systemmentioning

confidence: 99%

“…Many industries and production units can be enlisted where the importance of the level of the fluid stored in several tanks play significant role, for instance, in food processing units, dairy filtration, plants of nuclear power generations, companies dealing with pharmaceutical products, in system of water purification units, spray coating industries, etc. Furthermore, controlling the level of liquids in industries is also remarkably useful to enhance the economic beneficial and quality of the products prospects (e.g., [2]). In the practice this field is very rich and several design techniques have been developed in nonlinear control.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application of the Robust Fixed Point Iteration Method in Control of the Level of Twin Tanks Liquid

2020

View full text Add to dashboard Cite

Precise control of the flow rate of fluids stored in multiple tank systems is an important task in process industries. On this reason coupled tanks are considered popular paradigms in studies because they form strongly nonlinear systems that challenges the controller designers to develop various approaches. In this paper the application of a novel, Fixed Point Iteration (FPI)-based technique is reported to control the fluid level in a “lower tank” that is fed by the egress of an “upper” one. The control signal is the ingress rate at the upper tank. Numerical simulation results obtained by the use of simple sequential Julia code with Euler integration are presented to illustrate the efficiency of this approach.

show abstract

Section: Control Task Of the Dual Tank Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of the Robust Fixed Point Iteration Method in Control of the Level of Twin Tanks Liquid

2020

View full text Add to dashboard Cite

show abstract

“…Additionally, Nath et al used internal model control (IMC) to construct an auto-tuning level control loop with the goal of minimizing the discrepancy between the intended and measured levels, using twenty-five fuzzy rules for adaptive control. This approach is excellent for adjusting level control loops live, but it is computationally demanding and requires a large number of fuzzy rules, which is its primary drawback [25]. Shuyou Yu et al proposed a feed-forward controller and a feedback controller for the control level for three tank systems.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement-Learning-Based Level Controller for Separator Drum Unit in Refinery System

Ali

Rashid

Alhasnawi³

et al. 2023

Mathematics

View full text Add to dashboard Cite

The Basrah Refinery, Iraq, similarly to other refineries, is subject to several industrial constraints. Therefore, the main challenge is to optimize the parameters of the level controller of the process unit tanks. In this paper, a PI controller is designed for these important processes in the Basrah Refinery, which is a separator drum (D5204). Furthermore, the improvement of the PI controller is achieved under several constraints, such as the inlet liquid flow rate to tank (m2) and valve opening in yi%, by using two different techniques: the first one is conducted using a closed-Loop PID auto-tuner that is based on a frequency system estimator, and the other one is via the reinforcement learning approach (RL). RL is employed through two approaches: the first is calculating the optimal PI parameters as an offline tuner, and the second is using RL as an online tuner to optimize the PI parameters. In this case, the RL system works as a PI-like controller of RD5204. The mathematical model of the RD5204 system is derived and simulated using MATLAB. Several experiments are designed to validate the proposed controller. Further, the performance of the proposed system is evaluated under several industrial constraints, such as disturbances and noise, in which the results indict that RL as a tuner for the parameters of the PI controller is superior to other methods. Furthermore, using RL as a PI-like controller increases the controller’s robustness against uncertainty and perturbations.

show abstract

“…The closed loop asymptotic stability can be achieved with the NMPC approaches developed in theory. Yu et al 9 developed a controller composed of a feed-forward and feed-back controller for the three-tank systems. An improved cuckoo algorithm is proposed to solve the optimization problem involved in the developed nonlinear model predictive control.…”

Section: Introductionmentioning

confidence: 99%

Model-Predictive Control for the Three-Tank System Utilizing an Industrial Automation System

Kortela

2022

ACS Omega

View full text Add to dashboard Cite

A three-tank process has difficulty in controller design because of nonlinear flow and interactions between tanks. This paper addresses the design methodology of the model-predictive controller (MPC) for the three-tank system. The control performance of the proposed MPC controller is compared with the proportional plus integral (PI) controller by both simulations and experiments on the real three-tank pilot with the industrial ABB 800xA automation system. The MPC controller shows a faster response for the two tanks: In the simulation, the settling times are about 120 s for both tanks of the MPC controller. On the other hand, the settling times for the PI controller are about 200 s for the first tank and 150 s for the second tank. The experiments confirm these results.

show abstract

Liquid Level Tracking Control of Three-tank Systems

Cited by 15 publications

References 17 publications

Application of the Robust Fixed Point Iteration Method in Control of the Level of Twin Tanks Liquid

Application of the Robust Fixed Point Iteration Method in Control of the Level of Twin Tanks Liquid

Reinforcement-Learning-Based Level Controller for Separator Drum Unit in Refinery System

Model-Predictive Control for the Three-Tank System Utilizing an Industrial Automation System

Contact Info

Product

Resources

About