Multi-objective fuzzy fractional-order BELBIC for semi-active seismic control in non-linear building structures
Year: 2025
Type: article
Abstract: This study proposes a novel model-free Multi-Objective Fuzzy Fractional-Order BELBIC (MOFFO-BELBIC) algorithm to address the key gaps in semi-active seismic control of civil structures, unlike conventional single-input single-output (SISO) Brain emotional learning (BEL) controllers, which lack a holistic understanding of multi-loop structural control system dynamics. To bridge this gap, we introduce: (1) A novel multi-input multi-output (MIMO) BEL controller cascaded with a fractional order Proportional-Integral-Derivative controller (FOPID). (2): Offline hybrid multi-objective non-sorting genetic algorithm-III (NSGA-III) optimized Takagi-Sugeno-Kang (TSK) Fuzzy Inference System (FIS) tuning, (3): Online tuning through Fuzzy-to-Lookup table transformations, the trained FIS models are obtained adaptively to include the online training input-output pairs with optimal structural control performance, with 30 % cut down in computational cost. Therefore, MOFFO-BELBIC proposed an autonomous uncertainty handling solution specifically for nonlinear building structures without requiring retraining. To examine the efficacy of the proposed MOFFO-BELBIC algorithm, an illustrative example of a non-linear three-story benchmark building equipped with magnetorheological dampers is presented. The proposed MOFFO-BELBIC has shown a notable performance, 45–60 % superior response reduction compared with the modal-based and model-free control strategies presented in the past few decades.
Source: Engineering Structures
Authors: Muhammad Usman Saeed, Peizhen Li, Said Elias
Institutions: Tongji University, Leibniz University Hannover
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,620
OpenAlex ID: W4414015734