振动与冲击
振動與遲擊
진동여충격
JOURNAL OF VIBRATION AND SHOCK
2015年
2期
66-73
,共8页
铁路桥梁%磁流变脂阻尼器%模糊神经网络%改进的限幅最优控制%半主动控制
鐵路橋樑%磁流變脂阻尼器%模糊神經網絡%改進的限幅最優控製%半主動控製
철로교량%자류변지조니기%모호신경망락%개진적한폭최우공제%반주동공제
railway bridge%magneto rheological grease damper%fuzzy neural network%modified clipped-optimal control algorithm%semi-active control
为解决传统磁流变液阻尼器（Magneto Rheological Fluid Damper，MRFD）磁场利用率低及磁流变液沉降导致控制特性劣化难题，提出新型阻尼器—磁流变脂阻尼器（Magneto Rheological Grease Damper，MRGD）。采用神经网络（Neural Network，NN）对足尺 MRGD 动力特性进行辨识，通过将改进的限幅最优（Modified Clipped －Optimal，MCO）算法整合到模糊神经网络（Fuzzy Neral Network，FNN）理论来设计适合 MRGD 的 FNN ／MCO 半主动控制策略，并构建 SIMU-LINK 仿真分析平台。以典型三跨铁路连续梁桥为工程背景，分别对未控制、FNN ／MCO 半主动控制及线性二次型高斯（Linear Quadratic Gaussian，LQG）主动控制下桥梁各项评价指标进行分析。结果表明，所提 FNN ／MCO 半主动控制策略对桥梁地震响应控制效果明显优于 LQG 主动控制策略；FNN ／MCO 策略较 LQG 策略更利于控制装置性能发挥；FNN ／MCO策略稳定性、鲁棒性均明显优于 LQG 策略。
為解決傳統磁流變液阻尼器（Magneto Rheological Fluid Damper，MRFD）磁場利用率低及磁流變液沉降導緻控製特性劣化難題，提齣新型阻尼器—磁流變脂阻尼器（Magneto Rheological Grease Damper，MRGD）。採用神經網絡（Neural Network，NN）對足呎 MRGD 動力特性進行辨識，通過將改進的限幅最優（Modified Clipped －Optimal，MCO）算法整閤到模糊神經網絡（Fuzzy Neral Network，FNN）理論來設計適閤 MRGD 的 FNN ／MCO 半主動控製策略，併構建 SIMU-LINK 倣真分析平檯。以典型三跨鐵路連續樑橋為工程揹景，分彆對未控製、FNN ／MCO 半主動控製及線性二次型高斯（Linear Quadratic Gaussian，LQG）主動控製下橋樑各項評價指標進行分析。結果錶明，所提 FNN ／MCO 半主動控製策略對橋樑地震響應控製效果明顯優于 LQG 主動控製策略；FNN ／MCO 策略較 LQG 策略更利于控製裝置性能髮揮；FNN ／MCO策略穩定性、魯棒性均明顯優于 LQG 策略。
위해결전통자류변액조니기（Magneto Rheological Fluid Damper，MRFD）자장이용솔저급자류변액침강도치공제특성열화난제，제출신형조니기—자류변지조니기（Magneto Rheological Grease Damper，MRGD）。채용신경망락（Neural Network，NN）대족척 MRGD 동력특성진행변식，통과장개진적한폭최우（Modified Clipped －Optimal，MCO）산법정합도모호신경망락（Fuzzy Neral Network，FNN）이론래설계괄합 MRGD 적 FNN ／MCO 반주동공제책략，병구건 SIMU-LINK 방진분석평태。이전형삼과철로련속량교위공정배경，분별대미공제、FNN ／MCO 반주동공제급선성이차형고사（Linear Quadratic Gaussian，LQG）주동공제하교량각항평개지표진행분석。결과표명，소제 FNN ／MCO 반주동공제책략대교량지진향응공제효과명현우우 LQG 주동공제책략；FNN ／MCO 책략교 LQG 책략경리우공제장치성능발휘；FNN ／MCO책략은정성、로봉성균명현우우 LQG 책략。
In view of the problems of low utilization rate of magnetic field and degraded control characteristic due to sedimentation of magneto rheological fluid in traditional magneto rheological fluid damper (MRFD),magneto rheological grease damper (MRGD)as a new type of damper was proposed.The neural network (NN)was employed to identify the dynamic characteristics of a full-scale MRGD,the FNN /MCO semi-active control strategy for MRGD was designed by integrating the modified clipped-optimal (MCO) algorithm with the fuzzy neral network (FNN ) theory,and the SIMULINK simulation analysis platform corresponding to FNN /MCO strategy was constructed.Taking the typical three-span continuous girder railway bridge as engineering background,the various evaluation criteria for the bridge with non-control,FNN /MCO semi-active control and active control based on linear quadratic Gaussian (LQG)strategy were analyzed respectively.The analytical results show that the control effect on seismic responses of bridge with the FNN /MCO semi-active control strategy proposed is obviously superior to those with LQG active control strategy.Comparing with LQG strategy,the FNN /MCO strategy can more obviously contribute to the performance exertion of control devices.The stability and robustness of the FNN /MCO strategy are both superior to those of LQG control strategy.
