Application of Kalman filtering in optimized semi-active control of fixed metal platforms under earthquake

Abstract

Semi-active control is one of the most effective methods for damage reduction in offshore platforms subjected to intense environmental forces. Despite its advantages, probable device time delays may drastically decrease the real performance of the control algorithm. Thus, the uncertainty could make the control process non-optimal. In this paper, a Kalman Filter is used to ponder previous responses and the history of the measured errors in order to estimate the real state variables of an offshore structure equipped with Magneto-Rheological (MR) dampers. In the current article, the amount of applied voltage to the MR damper is optimized via the Adaptive Particle Swarm Optimization (APSO) method. Furthermore, the structure is controlled by the Linear–Quadratic Regulator (LQR) algorithm. A newly installed offshore platform, located in the Persian Gulf at a depth of 64 m is considered as an example to demonstrate the performance of the controller. The offshore structure is assumed to be excited by near- and far-field earthquakes. The results of the parametric studies indicate that all the earthquake-induced vibrations of the platform can be effectively suppressed by the designed control system. Moreover, the life spans of the dampers may increase with the predicting-optimizing algorithm.