• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.1
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• pp.103-112
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• 2007

Recently structures become longer and higher because of the developments of new materials and construction techniques. However, such modern structures are susceptible to excessive structural vibrations, which may induce problems of serviceability and structural damages. In this paper we attempt to control structural vibration using the probabilistic neural network(PNN) and the artificial neural network(ANN) based on the training pattern that consist of only the structural state vector and the control force. The state vectors of the structure and control forces made by linear quadratic regulator(LQR) algorithm are used for training pattern of PNN and ANN. The proposed algorithm is applied for the vibration control of the three story shear building under Northridge earthquake. Control results by the proposed PNN and ANN are compared with each other.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.3
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• pp.63-74
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• 1999

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.3
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• pp.99-106
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• 1998

The performance of the turbofan engine, a medium scale civil aircraft which has been developing in Rep. of Korea, was analyzed and the control scheme for optimization the performance was studied. The dynamic and real-time linear simulation was performed in the previous study The result was that the fuel scedule of the step increase overshoot the limit temperature(3105 $^{\cire}R$) of the high pressure turbine and got small surge margine of the high pressure compressor. Therefore a control scheme such as the LQR(Linear Quadratic Regulator) was applied to optimizing the performance in this studies. The linear model was expected for designing controller and the real time linear model was developed to be closed to nonlinear simulation results. The system matrices were derived from sampling operating points in the scheduled range and then the least square method was applied to the interpolation between these sampling points, where each element of matrices was a function of the rotor speed. The control variables were the fuel flow and the low pressure compressor bleed air. The controlled linear model eliminated the inlet temperature overshoot of the high pressure turbine and obtained maximum surge margins within 0.55. The SFC was stabilized in the range of 0.355 to 0.43.