研究了饱和输入下一类多项式系统的数据驱动控制问题.针对一类受噪声影响的未知多项式系统,设计了一种直接基于数据驱动的饱和控制器实现系统镇定,其中系统噪声具体形式未知但存在二次型上界.首先,在随机输入作用下离线采集系统的输入...研究了饱和输入下一类多项式系统的数据驱动控制问题.针对一类受噪声影响的未知多项式系统,设计了一种直接基于数据驱动的饱和控制器实现系统镇定,其中系统噪声具体形式未知但存在二次型上界.首先,在随机输入作用下离线采集系统的输入与输出数据.然后,通过采集到的离线数据以及平方和方法确定系统状态反馈控制器增益,引入的饱和约束机制可以对控制输入进行限幅.最后,通过在van der Pol振荡器系统中的数值仿真和电路实验验证了所提出控制策略的有效性.展开更多
The characters of limestone in weak interlayer of a high rocky slope in Xuzhou, China, are studied by shear static test and shear creep test. The results show that limestone specimens have attenuation creep properties...The characters of limestone in weak interlayer of a high rocky slope in Xuzhou, China, are studied by shear static test and shear creep test. The results show that limestone specimens have attenuation creep properties and constant rate creep properties, almost have no accelerated creep properties. The exponential type empirical formula is selected to fit creep grading curves by polynomial regression analysis method, and the square sums of the fitting results residual are in the order of 10^(-7). Then grade creep curves at every shear loads are set up. Combining creep rate-time curve, the creep properties of limestone are analyzed. As the physical meaning of component model is clearer, the Poytin–Thomson model is set up. Through the least square method, the optimal parameters of Poytin–Thomson model are obtained,and the sums of squared residuals belong to 10^(-3)order of magnitude, which can meet the accuracy requirements of engineering calculation. So the Poytin–Thomson model can reflect the shear creep characteristics of limestone very well.展开更多
The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are ...The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.展开更多
文摘研究了饱和输入下一类多项式系统的数据驱动控制问题.针对一类受噪声影响的未知多项式系统,设计了一种直接基于数据驱动的饱和控制器实现系统镇定,其中系统噪声具体形式未知但存在二次型上界.首先,在随机输入作用下离线采集系统的输入与输出数据.然后,通过采集到的离线数据以及平方和方法确定系统状态反馈控制器增益,引入的饱和约束机制可以对控制输入进行限幅.最后,通过在van der Pol振荡器系统中的数值仿真和电路实验验证了所提出控制策略的有效性.
基金funded by the State Key Development Program for Basic Research of China(No.2013CB227900)the Joint Funds of the National Natural Science Foundation of China(NoU1261201)Prof.Mao Xianbiao for his valuable assistance in the preparation of manuscript
文摘The characters of limestone in weak interlayer of a high rocky slope in Xuzhou, China, are studied by shear static test and shear creep test. The results show that limestone specimens have attenuation creep properties and constant rate creep properties, almost have no accelerated creep properties. The exponential type empirical formula is selected to fit creep grading curves by polynomial regression analysis method, and the square sums of the fitting results residual are in the order of 10^(-7). Then grade creep curves at every shear loads are set up. Combining creep rate-time curve, the creep properties of limestone are analyzed. As the physical meaning of component model is clearer, the Poytin–Thomson model is set up. Through the least square method, the optimal parameters of Poytin–Thomson model are obtained,and the sums of squared residuals belong to 10^(-3)order of magnitude, which can meet the accuracy requirements of engineering calculation. So the Poytin–Thomson model can reflect the shear creep characteristics of limestone very well.
基金supported by the National Natural Science Foundation of China (Nos. 51279186, 51479183, 51509227)the Shandong Province Natural Science Foundation, China (No. ZR2014EEQ030)the Fundamental Research Funds for the Central Universities (No. 201413003)
文摘The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.
