Emmanouil Alexis, Sebastian Espinel-Rios, Ioannis G. Kevrekidis, Jose L. Avalos
{"title":"Biochemical implementation of acceleration sensing and PIDA control","authors":"Emmanouil Alexis, Sebastian Espinel-Rios, Ioannis G. Kevrekidis, Jose L. Avalos","doi":"10.1101/2024.07.02.601775","DOIUrl":null,"url":null,"abstract":"Designing dependable, self-regulated biochemical systems has long posed a challenge in the field of Synthetic Biology. Here, we propose a realization of a Proportional- Integral-Derivative-Acceleration (PIDA) control scheme as a Chemical Reaction Network (CRN) governed by mass action kinetics. A constituent element of this architecture is a speed and acceleration biosensing mechanism we introduce and, subsequently, place within a feedback configuration. Our control scheme provides enhanced dynamic performance and robust steady-state tracking. In addition to our theoretical analysis, this is practically highlighted in both the deterministic and stochastic settings by regulating a specific biochemical process in-silico and drawing comparisons with a simpler PID controller.","PeriodicalId":501408,"journal":{"name":"bioRxiv - Synthetic Biology","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Synthetic Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.02.601775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Designing dependable, self-regulated biochemical systems has long posed a challenge in the field of Synthetic Biology. Here, we propose a realization of a Proportional- Integral-Derivative-Acceleration (PIDA) control scheme as a Chemical Reaction Network (CRN) governed by mass action kinetics. A constituent element of this architecture is a speed and acceleration biosensing mechanism we introduce and, subsequently, place within a feedback configuration. Our control scheme provides enhanced dynamic performance and robust steady-state tracking. In addition to our theoretical analysis, this is practically highlighted in both the deterministic and stochastic settings by regulating a specific biochemical process in-silico and drawing comparisons with a simpler PID controller.