A novel method based on ant colony optimization （ACO）, algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from th...A novel method based on ant colony optimization （ACO）, algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solu- tion problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACID algorithm. Finally, the ACID with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.展开更多
A new type of PID controller is introduced and some properties are given. The novelty of the proposed controller consists in the extension of derivation and integration order from integer to non-integer order. The PI...A new type of PID controller is introduced and some properties are given. The novelty of the proposed controller consists in the extension of derivation and integration order from integer to non-integer order. The PIλDμ controller generally has three advantages when compared to the integerl-order controller: the first is that it has more degrees of freedom in the model; the second is that it has a memory in model,the memory insure the history and its impact to present and future,the third is it ensures the stability of missile. This approach provides a more flexible tuning strategy and therefore an easier achieving of control requirements. Flight dynamic model of an aerodynamic missile is taken into account in implementing the PIλDμ controller. Simulation results show that the PIλDμ controller is not sensitive to the changes of control parameters and the system parameters. Also,the controller has more flexible structure and stronger robustness.展开更多
Terrain-aided navigation (TAN) uses terrain height variations under an aircraft to render the position estimate to bound the inertial navigation system (INS) error. This paper proposes a new terrain elevation matching...Terrain-aided navigation (TAN) uses terrain height variations under an aircraft to render the position estimate to bound the inertial navigation system (INS) error. This paper proposes a new terrain elevation matching(TEM) model, viz. Hidden-Markov-model(HMM) based TEM (HMMTEM) model. With the given model, an HMMTEM algorithm using Viterbi algorithm is designed and implemented to estimate the position error in INS. The simulation results show that HMMTEM algorithm can better improve the positioning precision of autonomous navigation than SITAN algorithm.展开更多
In this paper, we study the robust control for uncertain Markov jump linear singularly perturbed systems (MJLSPS), whose transition probability matrix is unknown. An improved heuristic algorithm is proposed to solve t...In this paper, we study the robust control for uncertain Markov jump linear singularly perturbed systems (MJLSPS), whose transition probability matrix is unknown. An improved heuristic algorithm is proposed to solve the nonlinear matrix inequalities. The results of this paper can apply not only to standard, but also to nonstandard MJLSPS. Moreover, the proposed approach is independent of the perturbation parameter and therefore avoids the ill-conditioned numerical problems.展开更多
A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on （fuzzy） cross-entropy（CE）. This algorithm is di...A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on （fuzzy） cross-entropy（CE）. This algorithm is divided into two parts： initial clustering process and incremental clustering process. The former calculates fuzzy cross-entropy or cross-entropy of one point relafive to others and a hierachical method based on cross-entropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the cross-entropy measure. Experimental compafisons show the proposed methood has lower time complexity than common methods in the large-scale data situations cr dynamic work environments.展开更多
文摘A novel method based on ant colony optimization （ACO）, algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solu- tion problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACID algorithm. Finally, the ACID with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.
文摘A new type of PID controller is introduced and some properties are given. The novelty of the proposed controller consists in the extension of derivation and integration order from integer to non-integer order. The PIλDμ controller generally has three advantages when compared to the integerl-order controller: the first is that it has more degrees of freedom in the model; the second is that it has a memory in model,the memory insure the history and its impact to present and future,the third is it ensures the stability of missile. This approach provides a more flexible tuning strategy and therefore an easier achieving of control requirements. Flight dynamic model of an aerodynamic missile is taken into account in implementing the PIλDμ controller. Simulation results show that the PIλDμ controller is not sensitive to the changes of control parameters and the system parameters. Also,the controller has more flexible structure and stronger robustness.
基金Supported by National Basic Research Program （973 Program） of China （2007CB724205）, National Natural Science Foundation of China （60604010）, and China Postdoctoral Science Foundation Funded Project （20080440384）
文摘Terrain-aided navigation (TAN) uses terrain height variations under an aircraft to render the position estimate to bound the inertial navigation system (INS) error. This paper proposes a new terrain elevation matching(TEM) model, viz. Hidden-Markov-model(HMM) based TEM (HMMTEM) model. With the given model, an HMMTEM algorithm using Viterbi algorithm is designed and implemented to estimate the position error in INS. The simulation results show that HMMTEM algorithm can better improve the positioning precision of autonomous navigation than SITAN algorithm.
基金National Excellent Doctoral Dissertation Foundation of P.R.China，National Natural Key Project for Basic Research of P.R.China，国家自然科学基金，清华大学校科研和教改项目
文摘In this paper, we study the robust control for uncertain Markov jump linear singularly perturbed systems (MJLSPS), whose transition probability matrix is unknown. An improved heuristic algorithm is proposed to solve the nonlinear matrix inequalities. The results of this paper can apply not only to standard, but also to nonstandard MJLSPS. Moreover, the proposed approach is independent of the perturbation parameter and therefore avoids the ill-conditioned numerical problems.
文摘A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on （fuzzy） cross-entropy（CE）. This algorithm is divided into two parts： initial clustering process and incremental clustering process. The former calculates fuzzy cross-entropy or cross-entropy of one point relafive to others and a hierachical method based on cross-entropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the cross-entropy measure. Experimental compafisons show the proposed methood has lower time complexity than common methods in the large-scale data situations cr dynamic work environments.
