This paper presents the modeling and control of a magnetorheological (MR) damper, installed in Chevron configuration, at the base of a 20-story benchmark building. The building structural model is created using the commercial software package ETABS. The MR damper model is derived from Bouc-Wen hysteresis model which provides the critical nonlinear dynamics that best represents the MR damper under a wide range of operating conditions. System identification is used to derive a low-order nonlinear model that best mimics the nonlinear dynamics of the actual MR damper. Dynamic behavior of this low-order model is tested and validated over a range of inputs. The damper model has proven its validity to a high degree of accuracy against the nonlinear model. A Kalman filter is designed to best estimate the state of the structure-damper system for feedback implementation purposes. Using the estimated states, an LQG-based compensator is designed to control the MR damper under earthquake loads. To demonstrate the effectiveness of this control strategy, four historical earthquakes are applied to the structure. Controlled and uncontrolled floor accelerations and displacements at key locations are compared. Results of the optimally controlled model demonstrate superior performance in comparison to the uncontrolled model.
To have reliable simulation of helicopter flight dynamics, high quality simulation models are needed. First principle modeling alone is not sufficient to obtain high quality reliable modles and therefore system identification is employed. Given a model structure, system identification techniques use data from flight test and estimate model parameters. These model parameters play critical role in estimating key helicopter parameters. This work uses system identifivcation techniques to estimate a Joker 3 helicopter critical flight parameters. The longitudinal and lateral short period oscillation frequencies and damping parameters, as well as the main rotor flapping time constant, are identified.The helicopter parameter were estimated using two different softeware packages and the results matched. Estimated parametyrs are comparable to those of similar size helicopter.
NomenclatureR =main rotor diameter. δcol = collective input. δlat = lateral cyclic input. δlon = longitudinal cyclic input. δped = pedal input. e = main rotor flapping time constant. nq = longitudinal dynamics natural frequency. np = lateral dynamics natural frequency. lon A =longitudinal cyclic to flap gain lat B =lateral cyclic to flap gain nom = nominal m.r. speed150 rad/s.
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