Multiple-model predictive control for component content of CePr/Nd countercurrent extraction process

Yang, Hui; Li, He; Zhang, Zhiyong; Lu, Ruochen; Tan, Chang

doi:10.1016/j.ins.2016.04.031

Cited by 18 publications

(9 citation statements)

References 16 publications

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“…Yang proposed the component content distribution profile control which can be automatically regulated by dynamically compensating the related extract or scrubbing liquid flow-rate 36 . Lu proposed a model based on generalized prediction of the content of rare earth extracted components to meet the demand of component content floating in a specific interval 37 . A paper applied Static Setting and dynamic compensation based optimal control strategy for the Flow Rate of the Reagent in Ce Pr/Nd Extraction Process 38 .…”

Section: Key Technologiesmentioning

confidence: 99%

Digital twin key technology on rare earth process

Yang

Kuang

Zhu

et al. 2022

Sci Rep

Self Cite

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Digital twin can be defined as a digital equivalent of an object of which it can mirror its behavior and status or virtual replicas of real physical entities in Cyberspace. To an extent, it also can simulate and predict the states of equipment or systems through smart algorithms and massive data. Hence, the digital twin is emerging used in intelligent manufacturing Systems in real-time and predicting system failure and also has introduced into a variety of traditional industries such as construction, Agriculture. Rare earth production is a typical process industry, and its Extraction Process enjoys the top priority in the industry. However, the extraction process is usually characterized by nonlinear behavior, large time delays, and strong coupling of various process variables. In case of failures happened in the process, the whole line would be shut down. Therefore, the digital twin is introduced into the design of process simulation to promote the efficiency and intelligent level of the Extraction Process. This paper proposes the techniques to build the rare earth digital twin such as soft measurement of component content, component content process simulation, control optimization strategy, and virtual workshop, etc. At the end, the validity of the model is verified, and a case study is conducted to verify the feasibility of the whole Digital twin framework.

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Section: Key Technologiesmentioning

confidence: 99%

Digital twin key technology on rare earth process

Yang

Kuang

Zhu

et al. 2022

Sci Rep

Self Cite

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show abstract

“…The multiple model strategy has been widely studied [26], such as the multiple model control system combined with a predictive controller [27]. For the switching mechanism of the multiple model strategy, the switching state selector is designed based on the fuzzy logic [28], and a Bayes theorem-based switching method is proposed [29].…”

Section: Design Of the Weighted Multiple Model Control System (Wmmcs)mentioning

confidence: 99%

“…The challenges of the multiple model control method are that the smooth switching performance and the practicability to each submodel are difficult to be simultaneously guaranteed. The switching method between operating status has been investigated previously [27][28][29]. However, conventional model switching strategies of the multiple model controller cannot maintain the smooth switching performance because the various matching variables with nonlinear characteristic are hard to be handled with.…”

Section: The Weighted Fusion Unit (Wfu)mentioning

confidence: 99%

Weighted multiple model control system for the stable steering performance of distributed drive electric vehicle

Shi

Yuan

Huang

et al. 2019

J Braz. Soc. Mech. Sci. Eng.

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The steering performance of the distributed drive electric vehicle (DDEV) is an important research topic. Generally, DDEV works under various operating status with high switching frequency, while the conventional stability controller is only suitable for one special operating status. In addition, the lateral force saturation or deficiency always leads to the unstable steering performance. To achieve the stable steering performance under various operating status for DDEV, a novel weighted multiple model control system (WMMCS) is proposed in this paper. The proposed WMMCS consists of three parts, including a submodel set (SMS), a subcontroller set (SCS) and a weighted fusion unit (WFU). The SMS classifies the vehicle operating status into four typical operating modes and analyses their operating characteristics. The SCS designs the corresponding model predictive controller for each typical operating mode to realize the optimal four-wheel steering; then, the lateral force saturation or deficiency problem can be solved. The WFU analyses the matching degree between the actual state of DDEV and each submodel by the fuzzy logic; then, the control output of the WMMCS is calculated by the weighted signal of each subcontroller. The simulation is carried on the MATLAB, and the results show that the stable steering performance and smooth operating switching performance of DDEV can be achieved efficiently by the proposed WMMCS.

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“…In other words, the designed controller can take an adaptive sampling strategy according to a priori knowledge for different system states. For instance, the aim of rare earth extraction process (REEP) is to obtain several high purity and high yield rare earth products by separating and extracting from mixed rare earth solution [23], [24]. It should be noted that the REEP is generally consisted of the extraction section composed by N stages mixer-settler and the scrubbing section composed by M stages mixer-settler in series.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sampling Dual Heuristic Dynamic Programming for Rare Earth Extraction Process

Jiang

Zhou

et al. 2019

IEEE Access

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Event-triggered control is applied to adaptive dynamic programming (ADP) as an effective method to reduce the computational cost, in which sampling only happens when a specific event occurs. In several cases of industrial applications, however, the sampling rate should be reduced in the given ranges where the prior knowledge of the process has been obtained. Correspondingly a greater sampled data are needed to observe the change of the control system more carefully if the controlled variables lie outside the boundary of the desired region. In response to this industrial demand, a novel adaptive sampling strategy according to a priori knowledge for different system states is proposed to reduce the sensitivity of the ADP-based methods. To implement the strategy into nonlinear continuous-time systems, an adaptive sampling condition is given. Furthermore, the stability analysis for the close-loop system is explicitly provided by using Lyapunov approach. The experimental results on the rare earth extraction process (REEP) verify the effectiveness of the proposed method.INDEX TERMS Adaptive dynamic programming (ADP), dual heuristic dynamic programming (DHP), adaptive sampling, rare earth extraction process.

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Multiple-model predictive control for component content of CePr/Nd countercurrent extraction process

Cited by 18 publications

References 16 publications

Digital twin key technology on rare earth process

Digital twin key technology on rare earth process

Weighted multiple model control system for the stable steering performance of distributed drive electric vehicle

Adaptive Sampling Dual Heuristic Dynamic Programming for Rare Earth Extraction Process

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