Performance Analysis of Fuzzy-PID Controller for Blood Glucose Regulation in Type-1 Diabetic Patients.
This paper presents Fuzzy-PID (FPID) control scheme for a blood glucose control of type 1 diabetic subjects. A new metaheuristic Cuckoo Search Algorithm (CSA) is utilized to optimize the gains of FPID controller. CSA provides fast convergence and is capable of handling global optimization of continu...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 12; pp. 1 - 16 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=118584394&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 118584394 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Dec2016 vid: 40 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 118584394 118584394 118584394 10.1007/s10916-016-0602-6 118584394 ppf: 1 ppct: 15 formats: fmt: @attributes: type: P tig: atl: Performance Analysis of Fuzzy-PID Controller for Blood Glucose Regulation in Type-1 Diabetic Patients. aug: au: Yadav, Jyoti Rani, Asha Singh, Vijander affil: Instrumentation and Control Engineering Division , NSIT , Sec-3, Dwarka New Delhi India sug: subj: Blood Glucose Medical Informatics Diabetes Mellitus Glycemic Control Human Models, Biological Algorithms Computer Simulation Data Analysis Software ab: This paper presents Fuzzy-PID (FPID) control scheme for a blood glucose control of type 1 diabetic subjects. A new metaheuristic Cuckoo Search Algorithm (CSA) is utilized to optimize the gains of FPID controller. CSA provides fast convergence and is capable of handling global optimization of continuous nonlinear systems. The proposed controller is an amalgamation of fuzzy logic and optimization which may provide an efficient solution for complex problems like blood glucose control. The task is to maintain normal glucose levels in the shortest possible time with minimum insulin dose. The glucose control is achieved by tuning the PID (Proportional Integral Derivative) and FPID controller with the help of Genetic Algorithm and CSA for comparative analysis. The designed controllers are tested on Bergman minimal model to control the blood glucose level in the facets of parameter uncertainties, meal disturbances and sensor noise. The results reveal that the performance of CSA-FPID controller is superior as compared to other designed controllers. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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