{"title":"Data enabled Predictive Control of LPV systems","authors":"Taleb Bou Hamdan , Patrick Coirault , Guillaume Mercère , Thibault Dairay","doi":"10.1016/j.conengprac.2024.105969","DOIUrl":null,"url":null,"abstract":"<div><p>This paper introduces a data-enabled predictive control methodology designed for Linear Parameter Varying (LPV) systems. By leveraging a polytopic representation of the LPV system, we formulate Willem’s lemma to accommodate parameter variations. The system trajectory is predicted over a finite horizon using specific trajectories generated offline. A notable advantage of this approach is its independence from <em>a priori</em> knowledge of parametric variations. Simulation studies conducted on both a numerical example and a simulator of a calendering process governed by partial differential equations substantiate the effectiveness of this approach.</p></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0967066124001291/pdfft?md5=5501daebef9e9159b80e070ffe5ee585&pid=1-s2.0-S0967066124001291-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066124001291","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces a data-enabled predictive control methodology designed for Linear Parameter Varying (LPV) systems. By leveraging a polytopic representation of the LPV system, we formulate Willem’s lemma to accommodate parameter variations. The system trajectory is predicted over a finite horizon using specific trajectories generated offline. A notable advantage of this approach is its independence from a priori knowledge of parametric variations. Simulation studies conducted on both a numerical example and a simulator of a calendering process governed by partial differential equations substantiate the effectiveness of this approach.
本文介绍了一种针对线性参数变化（LPV）系统设计的数据支持预测控制方法。通过利用 LPV 系统的多拓扑表示，我们提出了 Willem Lemma，以适应参数变化。系统轨迹是利用离线生成的特定轨迹在有限时间跨度内预测的。这种方法的一个显著优势是不受参数变化先验知识的影响。对偏微分方程控制的压延过程的数值示例和模拟器进行的模拟研究证实了这种方法的有效性。
期刊介绍：
Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper.
The scope of Control Engineering Practice matches the activities of IFAC.
Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.
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