A new fractional-order general type-2 fuzzy predictive control system and its application for glucose level regulation

Mohammadzadeh A., Kumbasar T.

APPLIED SOFT COMPUTING, vol.91, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 91
  • Publication Date: 2020
  • Doi Number: 10.1016/j.asoc.2020.106241
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Keywords: General Type-2 Fuzzy Logic Controller, Type-1 diabetes, Learning algorithm, Fractional-order, Stability analysis, ARTIFICIAL PANCREAS, MINIMAL-MODEL, LOGIC, SYNCHRONIZATION, OPTIMIZATION, ALGORITHM, DESIGN
  • Istanbul Technical University Affiliated: Yes


In this paper a new robust fractional-order predictive controller is presented and employed to regulate the glucose level in type-1 diabetes. The dynamics of the system is fully unknown an it is online estimated by a fractional-order model using interval Type-2 (T2) fuzzy logic system. The proposed control system is composed of two main controllers which are the predictive General T2 Fuzzy Logic Controller (GT2-FLC) and compensator controller. In this structure, the main controller is the GT2-FLC which is optimized via the Biogeography-based Optimization (BBO) algorithm such that to minimize a cost function in a fixed prediction horizon. The compensator controller is designed to guarantee the closed-loop asymptotic stability. The performance of proposed control strategy is examined on the modified Bergman's model of some patients with time-varying parameters, external noise perturbation and meal disturbances. The effectiveness of the proposed control scheme is verified and is compared with the other T2 fuzzy and well-known model predictive controllers. The results of the paper clearly show the superiority of the proposed T2 fuzzy logic control system. (C) 2020 Elsevier B.V. All rights reserved.