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شرح پروژه

سلام

rasoul sabetahd, [23.06.24 19:31]

سلام. وقت بخیر.

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عنوان و چکیده مقاله:

The Design of Online Adaptive FOPID Controller Optimized through the Interval Type-2 Fuzzy Neural Network by Using the Levenberg-Marquardt Algorithm for a 20-story Benchmark Building 

Abstract

The paper proposes an innovative control method for structures exposed to severe earthquakes, overcoming seismic uncertainties with remarkable accuracy. This method is crucial for controlling seismic response and ensuring structural stability. For this purpose, the robust adaptive FOPID controller is combined with the interval type-2 fuzzy neural network, whose parameters are optimized through the Levenberg-Marquardt Algorithm. An MLP neural network trained through an error backpropagation algorithm is considered for structural system identification and plant estimation. The Jacobian of the estimated model is used online to apply to the controller. Also, an adaptive compensator, type-2 interval fuzzy neural networks, is considered to increase the stability and robustness of the proposed controller against estimation error, seismic disturbances, and some unknown nonlinear functions. The Extended Kalman filter with feedback error learning strategy is used to maintain the acceptable performance level in the compensator. The performance effectiveness of the proposed controller equipped with a compensator in reducing seismic responses was investigated on a 20-story benchmark building equipped with an active cable damper, and the evaluation indices were compared with previous works. The results indicate that the IT2FNN-FOPID controller performs better than other controllers in mitigating seismic responses of the structure during an earthquake and achieving control objectives. So that the J_1 index in the El Centro earthquake with an intensity of 1.5 times has improved by about 70% of the ratio of the LQG controller, which is about 60% in the case of the Kobe earthquake.

Keywords: Benchmark Building; Adaptive control; FOPID controllers; Interval type-2 fuzzy neural networks; Multilayer Perceptron neural network; Levenberg–Marquardt Algorithm; Feedback error learning strategy.

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