A two degree of freedom level control

Wu, Kwo-Liang; Yu, Cheng‐Ching; Yao, Cheng

doi:10.1016/s0959-1524(00)00005-6

Cited by 30 publications

(19 citation statements)

References 10 publications

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“…Level processes generally do not have a dead time except for certain rare occasions such as level loops in which the control valve has a dead zone. Therefore, the dead time in level processes cannot be too large and has to be maintained at almost 10% of the hold-up time (Wu et al, 2001). Fig.…”

Section: Illustrative Examplesmentioning

confidence: 99%

“…However, it is quite complicated to determine the tuning parameters of a PI controller. Proportional-lag control (Luyben & Buckley, 1977) is a potentially good solution for liquid level control systems with feedforward compensation, but such feedforward control schemes (Luyben & Buckley, 1977;Wu, Yu, & Cheung, 2001) require an additional measurement which may be unavailable. Rivera, Morari, and Skogestad (1986) proposed the P-only controller using the internal model control (IMC) principle for the critically damped closed-loop response of a liquid level control system.…”

Section: Introductionmentioning

confidence: 99%

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Analytical design of a proportional-integral controller for constrained optimal regulatory control of inventory loop

Shin¹,

Lee²,

Park³

et al. 2008

Control Engineering Practice

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Section: Illustrative Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analytical design of a proportional-integral controller for constrained optimal regulatory control of inventory loop

Shin¹,

Lee²,

Park³

et al. 2008

Control Engineering Practice

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“…An expansion has been made to proportional-lag level control by load estimation for liquid level control in [14]. An automatic controller has been intended to control for the water level of a steam generator with no manual operation from start-up to full load transient conditions in [15].…”

Section: Introductionmentioning

confidence: 99%

A Real-Time Robust Fuzzy-based Level Control using Programmable Logic Controller

Aydoğmuş

2015

ElAEE

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Industrial software are specially designed to meet specific process. And sometimes this software can be very expensive. One way to reduce this cost is to develop own algorithm. This paper presents a real-time liquid level control implementation for an industrial process. The implementation of the level control is achieved using a fuzzy-based control algorithm. A Programmable Logic Controller (PLC) was used in which the fuzzy control algorithm has been embedded and can withstand against abrupt changes in the outlet flow. In addition, the fuzzy control algorithm is introduced to the system without a fuzzy module or software package. As a consequence, a robust and low cost liquid level control system has been realized. A Mamdani Fuzzy Inference System (MFIS) has been proposed. Membership functions of the input and output variables of the system were obtained and verified using Matlab/Simulink environment. The obtained functions have been used for the construction of fuzzy control algorithm in PLC. A robust fuzzy-based level controller has been achieved and quite satisfactory results were obtained in real-time implementation for different outlet flow rates.

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“…The (de-)tuning of PI controllers has been addressed in (Cheung and Luyben, 1979), (Kelly, 1998) and (Shin et al, 2008) amongst others. A control structure permitting separate responses to set-point and load disturbances were proposed by Wu et al (2001). The optimal non-linear continuous-and discrete-time controllers were derived in (McDonald et al, 1986) and in (Campo and Morari, 1989) respectively.…”

Section: Introductionmentioning

confidence: 99%

Practical Control of Surge Tanks Suffering from Frequent Inlet Flow Upsets

Rosander

Isaksson

Löfberg

et al. 2012

IFAC Proceedings Volumes

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In the presence of frequent inlet flow upsets, tuning of averaging level controllers is typically quite complicated since not only the size of the individual steps but also the time in between the subsequent steps need to considered. One structured way to achieve optimal filtering for such a case is to use Robust Model Predictive Control. The robust MPC controller is, however, quite computationally demanding and not easy to implement. In this paper two linear controllers, which mimic the behavior of the robust MPC are proposed. Tuning guidelines to avoid violation of the tank level constraints as well as to achieve optimal filtering are presented. Abstract: In the presence of frequent inlet flow upsets, tuning of averaging level controllers is typically quite complicated since not only the size of the individual steps but also the time in between the subsequent steps need to considered. One structured way to achieve optimal filtering for such a case is to use Robust Model Predictive Control. The robust MPC controller is, however, quite computationally demanding and not easy to implement. In this paper two linear controllers, which mimic the behavior of the robust MPC are proposed. Tuning guidelines to avoid violation of the tank level constraints as well as to achieve optimal filtering are presented.

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A two degree of freedom level control

Cited by 30 publications

References 10 publications

Analytical design of a proportional-integral controller for constrained optimal regulatory control of inventory loop

Analytical design of a proportional-integral controller for constrained optimal regulatory control of inventory loop

A Real-Time Robust Fuzzy-based Level Control using Programmable Logic Controller

Practical Control of Surge Tanks Suffering from Frequent Inlet Flow Upsets

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