R. Boffadossi, L. Fagiano, A. Cataldo, Marko Tanaskovic, M. Lauricella
{"title":"Advanced Hierarchical Predictive Routing Control of a smart de-manufacturing plant","authors":"R. Boffadossi, L. Fagiano, A. Cataldo, Marko Tanaskovic, M. Lauricella","doi":"10.23919/ecc54610.2021.9655105","DOIUrl":null,"url":null,"abstract":"The application of a novel approach to the routing control problem of a real de-manufacturing plant is presented. Named Hierarchical Predictive Routing Control (HPRC) and recently proposed in the literature, the approach deals with large number of integer inputs and complex temporal-logic constraints by adopting a low-level path-following strategy and a high-level predictive path allocation. Several improvements are presented, including a novel search tree exploration method, lockout detection routines, and plant-specific handling constraints. Simulation results show very good performance and small computational times even with high number of pallets and long prediction horizon values.","PeriodicalId":105499,"journal":{"name":"2021 European Control Conference (ECC)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 European Control Conference (ECC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ecc54610.2021.9655105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The application of a novel approach to the routing control problem of a real de-manufacturing plant is presented. Named Hierarchical Predictive Routing Control (HPRC) and recently proposed in the literature, the approach deals with large number of integer inputs and complex temporal-logic constraints by adopting a low-level path-following strategy and a high-level predictive path allocation. Several improvements are presented, including a novel search tree exploration method, lockout detection routines, and plant-specific handling constraints. Simulation results show very good performance and small computational times even with high number of pallets and long prediction horizon values.