Original scientific paper
https://doi.org/10.1080/00051144.2021.2003113
Decentralized robust interval type-2 fuzzy model predictive control for Takagi–Sugeno large-scale systems
Mohammad Sarbaz
; Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran
Iman Zamani
; Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran
Mohammad Manthouri
; Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran
Asier Ibeas
; Departament de Telecomunicació i Enginyeria de Sistemes, Escolad’Enginyeria, Universitat Autònoma de Barcelona, Barcelona, Spain
Abstract
Here, decentralized robust interval type-2 (IT2) fuzzy model predictive control (MPC) for Takagi–Sugeno (T-S) large-scale systems is studied. The large-scale system consists of many IT2 fuzzy T–S subsystems. Important necessities that limit the practical application of MPC are the online computational cost and burden of the frameworks. For MPC of T–S fuzzy large-scale systems, the online computational burden is even worse, and in some cases, they cannot be solved timely. Especially for severe, large-scale systems with disturbances, the MPC of T–S fuzzy large-scale systems usually give a conservative solution. So, researchers have many challenges and in finding a reasonable solution in a short time. Although more comfortable results can be achieved by the proposed fuzzy MPC approach, which adopts T–S large-scale systems with nonlinear subsystems, many restrictions are not considered. In this paper, challenges are solved, and the MPC is designed for a nonlinear IT2 fuzzy large-scale system with uncertainties and disturbances. Besides, the online optimization problem is solved, and results are proposed. Consequently, the online computational cost of the optimization problem is reduced considerably. Finally, the effectiveness of the proposed algorithm is illustrated with two practical examples.
Keywords
Large-scale systems; Interval type-2 fuzzy Takagi–Sugeno systems; Model predictive control
Hrčak ID:
286633
URI
Publication date:
26.12.2021.
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