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Advances in Concrete Construction
  Volume 13, Number 5, May 2022 , pages 385-394

Fuzzy neural network controller of interconnected method for civil structures
Z.Y. Chen, Yahui Meng, Ruei-yuan Wang and Timothy Chen

    Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for realtime implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.
Key Words
    civil structure; evolved algorithm; neural based LDI; structural health monitoring system
Z.Y. Chen, Yahui Meng, Ruei-yuan Wang: School of Science, Guangdong University of Petrochemical Technology, Maoming, Guangdong 525000, China
Timothy Chen: 2California Institute of Technology, Pasadena, CA 91125, USA

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