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Application of neural based fuzzy logic sliding mode control with moving sliding surface for the seismic isolation of a building with active tendon. (English) Zbl 1181.93035

Summary: In this study, neural based fuzzy sliding mode control algorithm is designed by putting advantageous specifications of sliding mode control and artificial intelligence techniques and applied to 8 storey sample building with active tendon. Performance of the designed controller is examined by applying acceleration data belonging to 6 earthquakes, each having different characteristics, as the external driving force. MATLAB software is used for numerical solutions, and the obtained results are compared in graphical form and presented in tables. A genetic algorithm is used for optimization process. Parametric uncertainities and time delay effects are considered. It is observed that performance of the controller is quite high and control force can be used practically. The obtained results also show that the controller provides quite successful control under earthquake effects having different characteristics.

MSC:

93B40 Computational methods in systems theory (MSC2010)
90C59 Approximation methods and heuristics in mathematical programming
92B20 Neural networks for/in biological studies, artificial life and related topics
86A15 Seismology (including tsunami modeling), earthquakes

Software:

Matlab
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