Semi-active LQG control of seismically excited nonlinear buildings using optimal Takagi-Sugeno inverse model of MR dampers

A novel semi-active control method for a seismically excited nonlinear benchmark building equipped with magnetorheological (MR) dampers is presented and evaluated in this paper. While Linear Quadratic Gaussian (LQG) controller is designed to estimate the optimal control force of a MR damper, the required voltage input for the damper to produce such control force is achieved by a proposed optimal Takagi-Sogeno(T-S) fuzzy inverse model. The proposed T-S fuzzy inverse model of dampers is derived using subtractive clustering, non-dominated sorting genetic algorithm II (NSGAII) and adaptive neuro-fuzzy inference systems (ANFIS). The effectiveness of this strategy is illustrated and verified using simulated response of a 20-storey full-scale nonlinear benchmark building excited by several historical earthquake records. The designed semi-active system is compared with the performances of active control as well as clipped optimal control (COC) systems, which are based on the same nominal controller as is used in this study. The results are discussed based on the evaluation criteria suggested for the benchmark problem by International Association for Structural Control and Monitoring (IASCM) for comparison with other algorithms and demonstrate the superiority of this scheme over other strategies.