混合遗传算法在结构动力反演中的应用研究
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摘要
研究了输入荷载未知条件下的结构参数识别及荷载反演问题,该问题最终归结为一个非线性的优化问题求解,根据目标函数、约束条件的具体特性,采用BFGS算法作为局部搜索算子,构造了基于浮点编码的混合遗传算法。针对系统输入未知的激励特性,采用分解反演的计算策略,从而提高了动力反演中混合遗传算法的稳健性和收敛速度。数值算例表明,这种方法具有很好的参数识别精度及荷载反演效果,对测试噪声有较强的适应能力。
In this paper, the structural parameter identification and the load identification of inverse analysis are studied. The resultant nonlinear global optimization problem is solved using a hybrid genetic algorithm in which the BFGS algorithm is chosen for local search. With no information of input excitation forces, a calculation strategy of decomposition inversion is presented, which improves the robustness and convergence rate of the hybrid genetic algorithm. Numerical simulation studies are performed. For verification purpose, both the noise-free and noise-included output responses are considered. Results show that the proposed method is efficient not only for structural parameter identification but also for load identification in inverse analysis.
In this paper, the structural parameter identification and the load identification of inverse analysis are studied. The resultant nonlinear global optimization problem is solved using a hybrid genetic algorithm in which the BFGS algorithm is chosen for local search. With no information of input excitation forces, a calculation strategy of decomposition inversion is presented, which improves the robustness and convergence rate of the hybrid genetic algorithm. Numerical simulation studies are performed. For verification purpose, both the noise-free and noise-included output responses are considered. Results show that the proposed method is efficient not only for structural parameter identification but also for load identification in inverse analysis.
引文
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[10]陈隽,李杰.系统非线性参数识别的松弛法[J].振动工程学报,2001,14(4):447-450.Chen Jun,Li Jie.Relaxation Method for nonlinear system parameter identification[J].Journal of Vibration Engineering,2001,14(4):447-450.(in Chinese)
[2]Liu Y,Kang L S,Evans D J.The annealing evolution algorithm as function optimizer[J].Parallel Computing,1995,21(3):389-400.
[3]陈国量,王煦法,庄镇泉.遗传算法及其应用[M].北京:人民邮电出版社,1993.Chen Guoliang,Wang Xufa,Zhuang Zhenquan.Genetic algorithm and its application[M].Beijing:Post and Telecommunication Press,1993.(in Chinese)
[4]赵明旺.连续可微函数全局优化的混合遗传算法[J].控制与决策,1997,12(5):589-592.Zhao Mingwang.A hybrid genetic algorithm for global optimization of continuous-differential functions[J].Control and Decision,1997,12(5):589-592.(in Chinese)
[5]王晓鹏.混合遗传算法及其在翼型气动多目标优化设计中的应用[J].空气动力学学报,2001,19(3):256-261.Wang Xiaopeng.Hybrid genetic algorithm and its application in multi-objective aerodynamic optimization design of airfoil[J].ACTA Aerodynamica Sinica,2001,19(3):256-261.(in Chinese)
[6]陈昌富,王贻荪,邹银生.边坡可靠性分析分步混合遗传算法[J].土木工程学报,2003,36(2):72-76.Chen Changfu,Wang Yisun,Zou Yinsheng.Two-stage hybrid genetic algorithm for slope reliability analysis[J].China Civil Engineering Journal,2003,36(2):72-76.(in Chinese)
[7]Hsiao Fan Wang,Kuang Yao Wu.Hybrid genetic algorithm for optimization problems with permutation property[J].Computers&Operations Research,2004,31(4):2453-2471.
[8]陈隽,李杰.部分输入未知条件下的结构系统识别研究[J].地震工程与工程振动,1998,18(4):40-47.Chen Jun,Li Jie.Study of structural system identifyication with incomplete input information[J].Earthquake Engineering and Engineering Vibration,1998,18(4):40-47.(in Chinese)
[9]李杰,陈隽.部分输入未知时求解动复合反演问题的补偿算法[J].计算力学学报,2002,19(3):310-314.Li Jie,Chen Jun.Compensation method for solving dynamical composite inversion problems with incomplete input information[J].Chinese Journal of Computational Mechanics,2002,19(3):310-314.
[10]陈隽,李杰.系统非线性参数识别的松弛法[J].振动工程学报,2001,14(4):447-450.Chen Jun,Li Jie.Relaxation Method for nonlinear system parameter identification[J].Journal of Vibration Engineering,2001,14(4):447-450.(in Chinese)
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