One-Spot Tuning PID Control of an Atmospheric Distillation Process

SICE Journal of Control, Measurement, and System Integration

2008

Self Cite

In petroleum refineries and petrochemical processes, the production cost reduction is a key matter in improving competitiveness. Previously, the authors proposed the cyclic one-spot tuning PID control scheme for single-input and single-output systems, and applied it to the atmospheric distillation tower. The effectiveness of the proposed control scheme has been verified in steady operation mode. However, satisfactory performance could not be obtained when the operation mode was switched to transition operation mode. In order to overcome this problem, it is necessary to consider the influence of the interactions upon each input and each output. This paper presents a new multiloop one-spot tuning PID control scheme with a static pre-compensator. According to the newly proposed control scheme, satisfactory control performance can be obtained in both the steady and the transition operation modes.

Section: Outline Of Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Design of a Multiloop One-Spot Tuning PID Controller and Its Application for a Crude Distillation Unit

SICE Journal of Control, Measurement, and System Integration

2008

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“…In order to overcome such problems, some advanced control technologies, e.g., model predictive control(MPC) [1] and dynamic matrix control(DMC) [2], have been developed in the last two decade. Authors have also proposed a new design method of PID control systems which are named cyclic one-spot tuning PID control(COST-PID) systems [3]- [5], and the effectiveness in both stationary and non-stationary states has been verified by applying it for the real atmospheric distillation tower(ADT). However, if the process van be highly stabilized by employing the COST-PID control method, the operating target or the operating mode is moved to the target where the profit can be further expected.…”

Section: Introductionmentioning

confidence: 99%

GMDH-Based Monitoring in an Atmospheric Distillation Process

Sakaguchi¹,

2006 SICE-ICASE International Joint Conference

2006

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In atmospheric distillation processes, the stabilization of processes is required in order to optimize the crudeoil composition corresponding to the product market conditions. However, the process control systems have sometimes fallen into unstable states in the case where unexpected disturbances are put into them, and the unusual phenomena have given undesirable influence on products. On the other hand, the useful chemical engineering model has not been established for these phenomena yet. This is still painful problem in the atmospheric distillation process now. This paper describes a new modeling scheme to predict the unusual phenomena in the atmospheric distillation process using the GMDH(Group Method of Data Handling) network which is one of network models. According to the GMDH network, the model structure can be determined systematically. However, the least squares method has been usually utilized in determining weight coefficients(model parameters). Then, the estimation accuracy is not expected so much, because the sum of squared errors between the measured values and estimates is evaluated. Therefore, instead of evaluating the sum of squared errors, the sum of absolute value of errors is introduced and the Levenberg-Marquardt method is employed in order to determine model parameters. The effectiveness of the proposed method is evaluated on the foaming prediction in the crude oil switching operation in the atmospheric distillation process.

“…In order to overcome problems of this type, advanced control technologies (e.g., model predictive control [MPC] [1] and dynamic matrix control [DMC] [2]) have been developed in the last two decades. The authors have also proposed a new design method for PID control systems, called cyclic one-spot tuning PID control (COST-PID) system [3][4][5], and its effectiveness in both stationary and nonstationary states has been verified by applying it to real atmospheric distillation towers (ADTs). However, if the process can be highly stabilized by employing the COST-PID control method, the operating target or the operating mode is moved to a target where profit can be further expected.…”

Section: Introductionmentioning

confidence: 99%

Development of a Nonlinear Soft Sensor Using a GMDH Network for a Refinery Crude Distillation Tower

Electrical Engineering Japan

2014

Self Cite

In atmospheric distillation processes, stabilization of processes is required in order to optimize the crude-oil composition that corresponds to product market conditions. However, the process control systems sometimes fall into unstable states in the case where unexpected disturbances are introduced, and these unusual phenomena have had an undesirable effect on certain products. Furthermore, a useful chemical engineering model has not yet been established for these phenomena. This remains a serious problem in atmospheric distillation processes. This paper describes a new modeling scheme to predict unusual phenomena in the atmospheric distillation process using a GMDH (Group Method of Data Handling) network, which is a type of network model. According to the GMDH network, the model structure can be determined systematically. However, the method of least squares has been commonly utilized in determining weight coefficients (model parameters). Estimation accuracy is not entirely essential, because the sum of the squared errors between the measured values and estimates is evaluated. Therefore, instead of evaluating the sum of the squared errors, the sum of the absolute values of the errors is introduced and the Levenberg-Marquardt method is employed in order to determine the model parameters. The effectiveness of the proposed method is evaluated by foaming prediction in the crude oil switching operation in the atmospheric distillation process. C⃝ 2014 Wiley Periodicals, Inc. Electr Eng Jpn, 188(3): 31-38, 2014; Published online in Wiley Online Library (wileyonlinelibrary.com).