结构主动控制的一体化多目标优化研究
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摘要
基于Pareto多目标遗传算法提出了结构主动控制系统的一体化多目标优化设计方法,对作动器位置与主动控制器进行同步优化设计。外界激励采用平稳过滤白噪声来模拟,在状态空间下通过求解Lyapunov方程,得到结构响应和主动控制力的均方值。主动控制器采用LQG控制算法来进行设计。以结构位移和加速度均方值最大值与相应无控响应均方值的最大值之比,以及所需控制力均方值之和作为多目标同步优化的目标函数。优化过程还考虑了结构与激励参数对优化结果的影响。最后以某6层平面框架有限元模型为例进行了计算机仿真分析,结果表明所提出的主动控制系统多目标一体化优化方法简单,高效,实用,具有较好的普适性。
This papers proposes a new integrated design and multi-objective optimization method for active control system based on a Pareto genetic algorithms,in which both the controller and actuator allocation can be optimized simultaneously.Random seismic excitation is simulated by the stationary filtered white noise,and then the Root-Mean Square(RMS) quantities of structural responses and active control forces are obtained by solving the Lyapunov equation in the state space.The controller is designed using LQG algorithm.Minimization of the maximal RMS displacement and acceleration,normalized by the uncontrolled counterparts,together with minimizing the sum of RMS control force of actuators,have been used as the three objective functions for multi-objective optimization.The influences of structural parameters and excitation characteristic are also considered in the multi-objective optimization procedure.A 6-story plane frame is used as a numerical example to demonstrate the effectiveness of the proposed method.Results show that the proposed integrated design and optimization method is simple,efficient and practical,and of good universality.
This papers proposes a new integrated design and multi-objective optimization method for active control system based on a Pareto genetic algorithms,in which both the controller and actuator allocation can be optimized simultaneously.Random seismic excitation is simulated by the stationary filtered white noise,and then the Root-Mean Square(RMS) quantities of structural responses and active control forces are obtained by solving the Lyapunov equation in the state space.The controller is designed using LQG algorithm.Minimization of the maximal RMS displacement and acceleration,normalized by the uncontrolled counterparts,together with minimizing the sum of RMS control force of actuators,have been used as the three objective functions for multi-objective optimization.The influences of structural parameters and excitation characteristic are also considered in the multi-objective optimization procedure.A 6-story plane frame is used as a numerical example to demonstrate the effectiveness of the proposed method.Results show that the proposed integrated design and optimization method is simple,efficient and practical,and of good universality.
引文
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[16]薛素铎,王雪生,曹资.基于新抗震规范的地震动随机模型参数研究[J].土木工程学报,2003,36(5):5—10.
[2]Chen G S,Bruno J,Salama M.Optimal placement ofactive/passive members in truss structures using sim-ulated annealing[J].AIAA Journal,1991,29(8):1 327—1 334.
[3]Liu X J,Begg D W,Matravers D R.Optimal topolo-gy/actuator placement design of structures using SA[J].Journal of Aerospace Engineering,1997,10(3):119—125.
[4]Abdullah M,Richardson A,Hanif J.Placement ofsensors/actuators on civil structures using genetic al-gorithms[J].Earthquake Engineering and StructuralDynamics,2001,30(8):1 167—1 184.
[5]Liu D K,Yang Y L,Li Q S.Optimum positioning ofactuators in tall buildings using genetic algorithm[J].Computers and Structures,2003,81:2 823—2 827.
[6]郭惠勇,蒋健,张陵.改进遗传算法在MRFD半主动控制系统优化配置中的应用[J].工程力学,2004,21(2):145—151.
[7]Li Q S,Liu D K,Tang J,Zhang N,Tam C M.Com-binatorial optimal design of number and positions ofactuators in actively controlled structures using genet-ic algorithms[J].Journal of Sound and Vibration,2004,270:611—624.
[8]Tan Ping,Dyke S J,Richardson A,et al.Integrateddevice placement and control design in civil structuresusing genetic algorithms[J].Journal of Structural En-gineering,ASCE,2005,131(10):1 489—1 496.
[9]Ahlawat A S,Rmaswamy A.Multi-objective optimalstructural vibration control using fuzzy logic controlsystem[J].Journal of Structural Engineering,2001,127(11):1 330—1 337.
[10]David A S,Paul N R,Lin Pei-yang.GA-optimizedfuzzy logic control of a large-scale building for seismicloads[J].Engineering Structures,2007,30(2):436—449.
[11]张连振,黄侨,王潮海.基于多目标遗传算法的传感器优化布点研究[J].工程力学,2007,24(4):168—172.
[12]Soong T T,Grigoriu M.Random Vibration of Me-chanical and Structural Systems[M].New Jersey:Prentice Hall,Englewood Cliffs,1992.
[13]张景绘,王超.工程随机振动理论[M].西安:西安交通大学出版社,1988.
[14]Deb K,Pratap A,Agrawal S,et al.A fast elitistmulti-objective genetic algorithm:NSGA-[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182—197.
[15]郑金华.多目标进化算法及其应用[M].北京:科学出版社,2007.
[16]薛素铎,王雪生,曹资.基于新抗震规范的地震动随机模型参数研究[J].土木工程学报,2003,36(5):5—10.
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