Controlling and Estimating the Speed of Shaking Table by Fusing Camera, Encoder and Accelerometer using ‎AUKF and Fuzzy Sliding Mode Controller

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.

کلیدواژه ها:

Earthquake Simulator ، ‎ ‎ Multi-Sensor Data Fusion ، ‎Fuzzy ، ‎ Sliding Mode Control ‎