Active Control with Optical Fiber Sensors and Neural Networks. I: Theoretical Analysis

Abstract

To implement the concept of a smart structure, a smart active control system is presented. Both fiber Bragg grating (FBG) sensors and neural networks are utilized to construct a system similar to the human being. The smart system is comprised of three parts: a structural condition surveillance system, three converters, and a controller. By distributing as many sensors as possible in the key areas in buildings, FBG sensors can be used for assessing structure soundness while acting as dendrites in a neural network system. Comparison of structural responses under an uncontrolled system, traditional optimal linear quadratic gain, and the proposed NEURO-FBG control system verifies the advantages of using this novel technique approach. The system robustness is evaluated under both time delay and disconnection problems. Analytical results demonstrate that the NEURO-FBG system can effectively control the response of the structure and provide a more reliable system than ordinary active control.