Design of model predictive control for industrial process with input time delay

Choomkasien, Pornthiwa; Chomphooyod, Peerawat; Banjerdpongchai, David

doi:10.23919/iccas.2017.8204305

Cited by 6 publications

(2 citation statements)

References 1 publication

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“…The calcination of cement is a complex and variable chemistry process, and the time delay in production seriously affects the accuracy of the model. For the time delays between process variables and f-CaO content, the complex industry leads to time delays that are difficult to be determined [27]. Due to different production situations, the time delay of the variables will change, and it is easy to ignore the time-varying characteristics of the time delay, and it is difficult to determine the length of time that has an actual impact on the target variable.…”

Section: Window Selection Mechanismmentioning

confidence: 99%

Soft sensor modeling of cement clinker quality: a novel timing matching technique and data decoupling approach

Zhao¹,

Wu²,

Zhang³

et al. 2023

Meas. Sci. Technol.

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Clinker f-CaO content is an important indicator of cement quality. Considering the production characteristics (strong coupling, time-varying delay) in the cement process industry, a soft sensor model was developed by combining various methods. First, a new decoupling method is proposed to deal with the strong coupling between variables, which achieves data decoupling between process variables through the attention mechanism and the LSTM network. Second, a novel time-series matching technique is proposed to handle the time-varying delays, which utilizes a window selection mechanism to adaptively select the time period in which each process variable influences the target variable. Third, the critical features of the variables are extracted by a one-dimensional convolution network(1D-CNN). Last, a combination of the data decoupling method, window selection mechanism, and 1D-CNN is applied to develop a soft sensor model (ADM-WGM-CNN), which implements the measurement of f-CaO content. The experimental results demonstrate that the ADM-WGM-CNN model has better measurement performance.

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Section: Window Selection Mechanismmentioning

confidence: 99%

Soft sensor modeling of cement clinker quality: a novel timing matching technique and data decoupling approach

Zhao¹,

Wu²,

Zhang³

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…e solution to the delay problem in remote is discussed in [28][29][30][31]. However, the local optimizer on the slave side of the robot will also cause a delay [32,33]. is part of the delay will also affect the remote operating system following the feedback signal.…”

Section: Introductionmentioning

confidence: 99%

The Design of Compact Robotic-Assisted Needle Position System with MPC-Based Remote Control

et al. 2020

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This article introduces the design and control performance of a lightweight, flexible, 4-degree-of-freedom (DOF) parallel robot for percutaneous biopsy guided by computed tomography (CT). At present, the CT guidance method allows surgeons to quickly locate the lesion area; however, it is necessary to manually adjust the position of the puncture needle for insertion. In this paper, a three-dimensional assisted method is used to infer the control input required to reach the target point through the kinematic model of the robot. A Kalman filter is designed to estimate model parameters and obtain a more accurate model. To further improve the control performance of the robot system, a model-based control method—the model predictive control (MPC) controller—is used to increase the accuracy of the needle position in the developed robot system. In this way, medical efficiency is improved while reducing the burden on the surgeon.

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Model predictive control with input disturbance and guaranteed Lyapunov stability for controller approximation

Wang

Zheng

2022

Sci. China Inf. Sci.

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Design of model predictive control for industrial process with input time delay

Cited by 6 publications

References 1 publication

Soft sensor modeling of cement clinker quality: a novel timing matching technique and data decoupling approach

Soft sensor modeling of cement clinker quality: a novel timing matching technique and data decoupling approach

The Design of Compact Robotic-Assisted Needle Position System with MPC-Based Remote Control

Model predictive control with input disturbance and guaranteed Lyapunov stability for controller approximation

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