Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Brief Fuzzy moving sliding mode control with application to robotic manipulators
Automatica (Journal of IFAC)
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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. 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.