In this paper, based on the second-order Taylor series expansion and the difference of convex functions algo- rithm for quadratic problems with box constraints （the DCA for QB）, a new method is proposed to solve the...In this paper, based on the second-order Taylor series expansion and the difference of convex functions algo- rithm for quadratic problems with box constraints （the DCA for QB）, a new method is proposed to solve the static response problem of structures with fairly large uncertainties in interval parameters. Although current methods are effective for solving the static response problem of structures with interval parameters with small uncertainties, these methods may fail to estimate the region of the static response of uncertain structures if the uncertainties in the parameters are fairly large. To resolve this problem, first, the general expression of the static response of structures in terms of structural parameters is derived based on the second-order Taylor series expansion. Then the problem of determining the bounds of the static response of uncertain structures is transformed into a series of quadratic problems with box constraints. These quadratic problems with box constraints can be solved using the DCA approach effectively. The numerical examples are given to illustrate the accuracy and the efficiency of the proposed method when comparing with other existing methods.展开更多
An interval optimization method for the dynamic response of structures with inter- val parameters is presented.The matrices of structures with interval parameters are given.Com- bining the interval extension with the ...An interval optimization method for the dynamic response of structures with inter- val parameters is presented.The matrices of structures with interval parameters are given.Com- bining the interval extension with the perturbation,the method for interval dynamic response analysis is derived.The interval optimization problem is transformed into a corresponding de- terministic one.Because the mean values and the uncertainties of the interval parameters can be elected design variables,more information of the optimization results can be obtained by the present method than that obtained by the deterministic one.The present method is implemented for a truss structure.The numerical results show that the method is effective.展开更多
Interval index structure plays an important role in constraint database systems. A dynamic interval index structure DM-tree is presented in this paper. The advantage of the DM-tree compared with other interval index ...Interval index structure plays an important role in constraint database systems. A dynamic interval index structure DM-tree is presented in this paper. The advantage of the DM-tree compared with other interval index structures is that the dynamic operations of insertion and deletion can be operated on the new structure. The storage complexity of the tree is O(n), and the query I/O complexity is O(log n+t/B). To improve the performance of the inserting and deleting operations, some methods such as neighbored-constraint and update-late are applied. The I / O complexity of inserting and deleting operations is the same as that in B-tree, i.e., O(log n).展开更多
Type-2 fuzzy controllers have been mostly viewed as black-box function generators. Revealing the analytical structure of any type-2 fuzzy controller is important as it will deepen our understanding of how and why a ty...Type-2 fuzzy controllers have been mostly viewed as black-box function generators. Revealing the analytical structure of any type-2 fuzzy controller is important as it will deepen our understanding of how and why a type-2 fuzzy controller functions and lay a foundation for more rigorous system analysis and design. In this study, we derive and analyze the analytical structure of an interval type-2 fuzzy controller that uses the following identical elements: two nonlinear interval type-2 input fuzzy sets for each variable, four interval type-2 singleton output fuzzy sets, a Zadeh AND operator, and the Karnik-Mendel type reducer. Through dividing the input space of the interval type-2 fuzzy controller into 15 partitions, the input-output relationship for each local region is derived. Our derivation shows explicitly that the controller is approximately equivalent to a nonlinear proportional integral or proportional differential controller with variable gains. Furthermore, by comparing with the analytical structure of its type-1 counterpart, potential advantages of the interval type-2 fuzzy controller are analyzed. Finally, the reliability of the analysis results and the effectiveness of the interval type-2 fuzzy controller are verified by a simulation and an experiment.展开更多
基金supported by the National Natural Science Foundation of China (Grants 11002013, 11372025)the Defense Industrial Technology Development Program (Grants A0820132001, JCKY2013601B)+1 种基金the Aeronautical Science Foundation of China (Grant 2012ZA51010)111 Project (Grant B07009) for support
文摘In this paper, based on the second-order Taylor series expansion and the difference of convex functions algo- rithm for quadratic problems with box constraints （the DCA for QB）, a new method is proposed to solve the static response problem of structures with fairly large uncertainties in interval parameters. Although current methods are effective for solving the static response problem of structures with interval parameters with small uncertainties, these methods may fail to estimate the region of the static response of uncertain structures if the uncertainties in the parameters are fairly large. To resolve this problem, first, the general expression of the static response of structures in terms of structural parameters is derived based on the second-order Taylor series expansion. Then the problem of determining the bounds of the static response of uncertain structures is transformed into a series of quadratic problems with box constraints. These quadratic problems with box constraints can be solved using the DCA approach effectively. The numerical examples are given to illustrate the accuracy and the efficiency of the proposed method when comparing with other existing methods.
基金Project supported by the National Natural Science Foundation of China(No.10202006).
文摘An interval optimization method for the dynamic response of structures with inter- val parameters is presented.The matrices of structures with interval parameters are given.Com- bining the interval extension with the perturbation,the method for interval dynamic response analysis is derived.The interval optimization problem is transformed into a corresponding de- terministic one.Because the mean values and the uncertainties of the interval parameters can be elected design variables,more information of the optimization results can be obtained by the present method than that obtained by the deterministic one.The present method is implemented for a truss structure.The numerical results show that the method is effective.
基金Supported by the National Natural Science Foundation of China under grant !Nos.69933010 and69773012.
文摘Interval index structure plays an important role in constraint database systems. A dynamic interval index structure DM-tree is presented in this paper. The advantage of the DM-tree compared with other interval index structures is that the dynamic operations of insertion and deletion can be operated on the new structure. The storage complexity of the tree is O(n), and the query I/O complexity is O(log n+t/B). To improve the performance of the inserting and deleting operations, some methods such as neighbored-constraint and update-late are applied. The I / O complexity of inserting and deleting operations is the same as that in B-tree, i.e., O(log n).
基金supported by the Xinjiang Astronomical Observatory,China(No.2014KL012)the Major State Basic Research Development Program of China(No.2015CB857100)+1 种基金the National Natural Science Foundation of China(Nos.51490660 and 51405362)the Fundamental Research Funds for the Central Universities,China(No.SPSY021401)
文摘Type-2 fuzzy controllers have been mostly viewed as black-box function generators. Revealing the analytical structure of any type-2 fuzzy controller is important as it will deepen our understanding of how and why a type-2 fuzzy controller functions and lay a foundation for more rigorous system analysis and design. In this study, we derive and analyze the analytical structure of an interval type-2 fuzzy controller that uses the following identical elements: two nonlinear interval type-2 input fuzzy sets for each variable, four interval type-2 singleton output fuzzy sets, a Zadeh AND operator, and the Karnik-Mendel type reducer. Through dividing the input space of the interval type-2 fuzzy controller into 15 partitions, the input-output relationship for each local region is derived. Our derivation shows explicitly that the controller is approximately equivalent to a nonlinear proportional integral or proportional differential controller with variable gains. Furthermore, by comparing with the analytical structure of its type-1 counterpart, potential advantages of the interval type-2 fuzzy controller are analyzed. Finally, the reliability of the analysis results and the effectiveness of the interval type-2 fuzzy controller are verified by a simulation and an experiment.
