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  1. Book ; Online: Robust Data-Driven Predictive Control for Unknown Linear Time-Invariant Systems

    Hu, Kaijian / Liu, Tao

    2024  

    Abstract: This paper presents a new robust data-driven predictive control scheme for unknown linear time-invariant systems by using input-state-output or input-output data based on whether the state is measurable. To remove the need for the persistently exciting ( ... ...

    Abstract This paper presents a new robust data-driven predictive control scheme for unknown linear time-invariant systems by using input-state-output or input-output data based on whether the state is measurable. To remove the need for the persistently exciting (PE) condition of a sufficiently high order on pre-collected data, a set containing all systems capable of generating such data is constructed. Then, at each time step, an upper bound of a given objective function is derived for all systems in the set, and a feedback controller is designed to minimize this bound. The optimal control gain at each time step is determined by solving a set of linear matrix inequalities. We prove that if the synthesis problem is feasible at the initial time step, it remains feasible for all future time steps. Unlike current data-driven predictive control schemes based on behavioral system theory, our approach requires less stringent conditions for the pre-collected data, facilitating easier implementation. Further, the proposed predictive control scheme features an infinite prediction horizon, potentially resulting in superior overall control performance compared to existing methods with finite prediction horizons. The effectiveness of our proposed methods is demonstrated through application to an unknown and unstable batch reactor.
    Keywords Electrical Engineering and Systems Science - Systems and Control
    Subject code 515
    Publishing date 2024-01-14
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Effect of Ecologically Restored Vegetation Roots on the Stability of Shallow Aggregates in Ionic Rare Earth Tailings Piles

    Zhong, Wen / Shuai, Qi / Zeng, Peng / Guo, Zhongqun / Hu, Kaijian / Wang, Xiaojun / Zeng, Fangjin / Zhu, Jianxin / Feng, Xiao / Lin, Shengjie / Feng, Zhiqi

    Agronomy. 2023 Mar. 28, v. 13, no. 4

    2023  

    Abstract: Aggregate stability is considered an essential indicator of changes in the physical properties of soils, and vegetation roots play a crucial role in the stability of shallow soil aggregates in ionic rare earth tailings piles during ecological remediation. ...

    Abstract Aggregate stability is considered an essential indicator of changes in the physical properties of soils, and vegetation roots play a crucial role in the stability of shallow soil aggregates in ionic rare earth tailings piles during ecological remediation. In this paper, the influence of the law of ecologically restored vegetation roots on the stability of shallow aggregates of ionic rare earth tailing piles was investigated by means of field investigation tests, indoor experiments and mathematical statistics. The influence of different types of root systems on the stability of the shallow depth range aggregates of tailings piles was investigated; the correlation between vegetation root systems and the main physical parameters of rare earth tailings was clarified; and a mathematical correlation model characterizing the characteristic parameters of vegetation root systems was constructed. The evaluation index of the stability of rare earth tailings piles was constructed, and the influence of the law of the ecological restoration of vegetation root systems on the strength of shallow aggregates of ionic rare earth tailings piles was revealed. The results of the study showed that compared with the RD (root density), the root characteristic parameter with the largest response weight to the rare earth tailings pile is the RL (root length density), and the root characteristic parameter with the largest response weight to the water content is the RV (root volume). Suitable vegetation roots can effectively enhance the content of shallow large aggregates of rare ionic earth tailing piles. With the increase of the depth of a tailing pile, the content of large aggregates continues to decrease, and the content of micro aggregates continues increasing. This indicates that the vegetation root system changed the shallow soil of the rare earth tailing pile from disorderly to orderly through its own growth pattern, which effectively improved the stability of the shallow aggregates of the tailing pile and improved the physical properties of the tailing.
    Keywords aggregate stability ; agronomy ; ecological restoration ; models ; remediation ; root systems ; statistics ; vegetation ; water content
    Language English
    Dates of publication 2023-0328
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ZDB-ID 2607043-1
    ISSN 2073-4395
    ISSN 2073-4395
    DOI 10.3390/agronomy13040993
    Database NAL-Catalogue (AGRICOLA)

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  3. Article: Dynamic pore structure evolution of the ion adsorbed rare earth ore during the ion exchange process.

    Zhou, Lingbo / Wang, Xiaojun / Zhuo, Yulong / Hu, Kaijian / Zhong, Wen / Huang, Guangli

    Royal Society open science

    2019  Volume 6, Issue 11, Page(s) 191107

    Abstract: During the leaching process of the ion-adsorbed rare earth (RE) ore, the pore structure evolution of the ore body plays a vital role in the seepage of the leaching solution. To investigate the evolution of the pore structure during the leaching process, ... ...

    Abstract During the leaching process of the ion-adsorbed rare earth (RE) ore, the pore structure evolution of the ore body plays a vital role in the seepage of the leaching solution. To investigate the evolution of the pore structure during the leaching process, experiments have been carried out with remodelled RE ore samples based on the physical characteristics of
    Language English
    Publishing date 2019-11-06
    Publishing country England
    Document type Journal Article
    ZDB-ID 2787755-3
    ISSN 2054-5703
    ISSN 2054-5703
    DOI 10.1098/rsos.191107
    Database MEDical Literature Analysis and Retrieval System OnLINE

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