Control
Nima Rajabi; Ramezan Havangi; Amir Hossein ‎ Abolmasoumi
Abstract
An earthquake is a sudden and destructive natural disaster that often results in unpredictable damage to human life and property. Investigating the effects of earthquakes on buildings and enhancing the seismic performance of structures is a crucial approach for mitigating severe damage ...
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An earthquake is a sudden and destructive natural disaster that often results in unpredictable damage to human life and property. Investigating the effects of earthquakes on buildings and enhancing the seismic performance of structures is a crucial approach for mitigating severe damage during such events. One effective tool in testing the resistance of structures against earthquakes is the use of shaking tables. In this paper, the stabilization and control of earthquake simulator using a fuzzy sliding mode controller (FSMC) and adaptive unscented Kalman filter (AUKF)and adaptive extended Kalman filter (AEKF) is presented. These filters employ a recursive technique to effectively adjust the noise covariance by utilizing an adaptation method known as the steepest descent. In the proposed approach, the shaking table states are estimated using an accelerometer, encoder, and camera. These estimated states are then utilized by the AEKF/AUKF to stabilize and control the closed-loop system. A fuzzy sliding mode controller is designed to track the reference input, and eliminate external disturbances and noise. In the control of sliding mode, the occurrence of chattering in the control input is unavoidable. To mitigate this undesired chattering phenomenon, a fuzzy inference mechanism has been employed. The image processing approach has been utilized to measure the displacement online using the camera. The advantages of using the camera include not requiring direct contact with the table, as well as offering a low price and good accuracy.
