Intelligent fuzzy optimal control of building structures

This paper describes an optimal adaptive and predictive control system and its digital simulations for a five-degree-of-freedom system subjected to earthquake loading. In this system, an active mass driver system and an equivalent variable mass system are employed as an active control method. Prediction of earthquake input and structural identification are performed by using neural networks based on the error back-propagation method. To get appropriate training data for structural identification, the genetic algorithm is employed. Optimization is performed by means of macimizing decision. In maximizing decision, optimal target control variables are determined by using assumed membership functions of target responses. Results of digital simulations show the effectiveness of the proposed control system.