Semi-active vibration control of building structure by Self Tuned Brain Emotional Learning Based Intelligent Controller

Abstract

Control algorithms are the most crucial aspects in effective control of civil structures exposed to earthquake forces. Recently, adaptive intelligent control algorithms are evolving to be a viable substitute strategy for conventional model-based control algorithms. One of the most recent developments, known as the Brain Emotional Learning Based Intelligent Controller (BELBIC), has caught the attention of scientists as a model-free adaptive control system. It possesses appealing capabilities for dealing with nonlinearities and uncertainties in control frameworks. The modern semi-actively controlled civil structures have a highly uncertain and nonlinear nature following severe disturbances. As a result, these structures require real-time (online) robust control actions towards changing conditions, which the controllers with rigid settings cannot adapt. This study intends to overcome this issue in two ways: an online self-tuning brain emotional learning-based intelligent controller (ST-BELBIC) is formulated. Then its capabilities in improving the performance of cascaded controller in attenuating seismic vibrations of a three-story scaled building structure are validated. In this case, the central control unit BELBIC is based on sensory inputs (SI) and emotional cues (reward) signals. The main contribution of the proposed controller is a self-attuned version of the standard BELBIC that uses the benefits of a first-order Sugano fuzzy inference system (FIS) to adapt its parameters online. The proposed control methodology can be a promising model-free controller in terms of online tuning, simplicity of configuration, ease of applicability, less operational time, and neutralizing nonlinearities. The simulation affirms that the proposed controller compared with conventional LQR and intelligent Fuzzy tuned PID (FT-PID) controllers shows a superior performance regarding attenuating seismic responses of the building and can also improve the performance of cascaded FT-PID controller.