目前,直流微电网在全球范围内快速发展,开展充分的稳定性分析工作是其稳定运行的前提。伴随着大量电力电子装置的接入,相较于传统电网,直流微电网系统等效惯性不足,在经历电网故障、电压暂降或恒功率负载接入接出等大扰动场景后,其状态...目前,直流微电网在全球范围内快速发展,开展充分的稳定性分析工作是其稳定运行的前提。伴随着大量电力电子装置的接入,相较于传统电网,直流微电网系统等效惯性不足,在经历电网故障、电压暂降或恒功率负载接入接出等大扰动场景后,其状态变量易发生大范围变化,暂态稳定性问题突出。Lyapunov方法是分析暂态稳定性问题的常用方法,但在直流微电网领域中缺少指导构建Lyapunov函数的通用策略,很难直接进行应用。此外,为了提高稳定性,亟待开展以提升暂态稳定性为导向的控制参数优化设计研究。针对以上问题,针对直流微电网系统,考虑DC-DC变换器控制环路,基于平方和(sum of squares,SOS)规划方法开展暂态稳定域估计与参数优化研究,首先,通过设计SOS优化问题,改进传统拓展内部算法求解并获得最大化Lyapunov函数水平集实现对系统稳定域的估计,通过与系统实际稳定域进行对比,验证了所提方法的准确性,与其他现有方法估计的稳定域相比,所提方法保守性大幅降低。随后,基于SOS规划,以拓展稳定域为目标,对电压控制环路参数进行优化。最后,硬件在环仿真实验结果表明,采用优化控制参数后,直流微电网系统稳定域得到扩展,抗扰动能力有效提升,暂态稳定性进一步增强。展开更多
针对具有不确定干扰的汽轮发电机励磁与汽阀综合控制系统,建立鲁棒综合控制模型。运用基于Sum of Squares(SOS)分解技术的鲁棒控制方法(SOSRCA),设计电力系统鲁棒综合控制方法。该方法充分考虑了综合系统中存在的不确定参数及干扰,使发...针对具有不确定干扰的汽轮发电机励磁与汽阀综合控制系统,建立鲁棒综合控制模型。运用基于Sum of Squares(SOS)分解技术的鲁棒控制方法(SOSRCA),设计电力系统鲁棒综合控制方法。该方法充分考虑了综合系统中存在的不确定参数及干扰,使发电机组具有较好的鲁棒性能。控制方法的求解过程是算法化、程序化的,避免了繁琐的递归设计和参数估计过程。最后,在三机电力系统仿真中,对基于SOSRCA所得出的鲁棒综合控制律进行仿真分析与讨论,验证其有效性及优越性。展开更多
Nonlinear time series prediction is studied by using an improved least squares support vector machine （LSSVM） regression based on chaotic mutation evolutionary programming （CMEP） approach for parameter optimizatio...Nonlinear time series prediction is studied by using an improved least squares support vector machine （LSSVM） regression based on chaotic mutation evolutionary programming （CMEP） approach for parameter optimization. We analyze how the prediction error varies with different parameters （σ, γ） in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.展开更多
We present a procedure that gives us an SOS (sum of squares) decomposition of a given real polynomial in variables, if there exists such decomposition. For the case of real polynomials in non-commutative variables we ...We present a procedure that gives us an SOS (sum of squares) decomposition of a given real polynomial in variables, if there exists such decomposition. For the case of real polynomials in non-commutative variables we extend this procedure to obtain a sum of hermitian squares SOHS) decomposition whenever there exists any. This extended procedure is the main scientific contribution of the paper.展开更多
Time-differences-of-arrival （TDOA） and gain-ratios-of- arrival （GROA） measurements are used to determine the passive source location. Based on the measurement models, the con- strained weighted least squares （CWL...Time-differences-of-arrival （TDOA） and gain-ratios-of- arrival （GROA） measurements are used to determine the passive source location. Based on the measurement models, the con- strained weighted least squares （CWLS） estimator is presented. Due to the nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem （SDP）, which can be solved by using modern convex optimization algorithms. Moreover, this relaxation can be proved to be tight, i.e., the SDP solves the relaxed CWLS problem, and this hence guarantees the good per- formance of the proposed method. Furthermore, this method is extended to solve the localization problem with sensor position errors. Simulation results corroborate the theoretical results and the good performance of the proposed method.展开更多
By attacking the linear programming problems from their dual side,a new general algorithm for linear programming is developed.At each iteration,the algorithm finds a feasible descent search direction by handling a lea...By attacking the linear programming problems from their dual side,a new general algorithm for linear programming is developed.At each iteration,the algorithm finds a feasible descent search direction by handling a least square problem associated with the dual system,using QR decomposition technique.The new method is a combination of pivot method and interior-point method.It in fact not only reduces the possibility of difficulty arising from degeneracy,but also has the same advantages as pivot method in warm-start to resolve linear programming problems.Numerical results of a group of randomly constructed problems are very encouraging.展开更多
The definition of generalized unified (C, α, ρ, d)-convex function is given. The concepts of generalized unified (C, α, ρ, d)-quasiconvexity, generalized unified (C, α, ρ, d)-pseudoconvexity and generalized unif...The definition of generalized unified (C, α, ρ, d)-convex function is given. The concepts of generalized unified (C, α, ρ, d)-quasiconvexity, generalized unified (C, α, ρ, d)-pseudoconvexity and generalized unified (C, α, ρ, d)-strictly pseudoconvex functions are presented. The sufficient optimality conditions for multiobjective nonsmooth semi-infinite programming are obtained involving these generalized convexity lastly.展开更多
In the time-difference-of-arrival(TDOA)localization,robust least squares(LS)problems solved by mathematical programming were proven to be superior in mitigating the effects of non-line-of-sight(NLOS)propagation.Howeve...In the time-difference-of-arrival(TDOA)localization,robust least squares(LS)problems solved by mathematical programming were proven to be superior in mitigating the effects of non-line-of-sight(NLOS)propagation.However,the existing algorithms still suffer from two disadvantages:1)The algorithms strongly depend on prior information;2)The approaches do not satisfy the mean square error(MSE)optimal criterion of the measurement noise.To tackle the troubles,we first formulate an MSE minimization model for measurement noise by taking the source and the NLOS biases as variables.To obtain stable solutions,we introduce a penalty function to avoid abnormal estimates.We further tackle the nonconvex locating problem with semidefinite relaxation techniques.Finally,we incorporate mixed constraints and variable information to improve the estimation accuracy.Simulations and experiments show that the proposed method achieves consistent performance and good accuracy in dynamic NLOS environments.展开更多
文摘目前,直流微电网在全球范围内快速发展,开展充分的稳定性分析工作是其稳定运行的前提。伴随着大量电力电子装置的接入,相较于传统电网,直流微电网系统等效惯性不足,在经历电网故障、电压暂降或恒功率负载接入接出等大扰动场景后,其状态变量易发生大范围变化,暂态稳定性问题突出。Lyapunov方法是分析暂态稳定性问题的常用方法,但在直流微电网领域中缺少指导构建Lyapunov函数的通用策略,很难直接进行应用。此外,为了提高稳定性,亟待开展以提升暂态稳定性为导向的控制参数优化设计研究。针对以上问题,针对直流微电网系统,考虑DC-DC变换器控制环路,基于平方和(sum of squares,SOS)规划方法开展暂态稳定域估计与参数优化研究,首先,通过设计SOS优化问题,改进传统拓展内部算法求解并获得最大化Lyapunov函数水平集实现对系统稳定域的估计,通过与系统实际稳定域进行对比,验证了所提方法的准确性,与其他现有方法估计的稳定域相比,所提方法保守性大幅降低。随后,基于SOS规划,以拓展稳定域为目标,对电压控制环路参数进行优化。最后,硬件在环仿真实验结果表明,采用优化控制参数后,直流微电网系统稳定域得到扩展,抗扰动能力有效提升,暂态稳定性进一步增强。
文摘针对具有不确定干扰的汽轮发电机励磁与汽阀综合控制系统,建立鲁棒综合控制模型。运用基于Sum of Squares(SOS)分解技术的鲁棒控制方法(SOSRCA),设计电力系统鲁棒综合控制方法。该方法充分考虑了综合系统中存在的不确定参数及干扰,使发电机组具有较好的鲁棒性能。控制方法的求解过程是算法化、程序化的,避免了繁琐的递归设计和参数估计过程。最后,在三机电力系统仿真中,对基于SOSRCA所得出的鲁棒综合控制律进行仿真分析与讨论,验证其有效性及优越性。
基金The project supported by National Natural Science Foundation of China under Grant No. 90203008 and the Doctoral Foundation of the Ministry of Education of China
文摘Nonlinear time series prediction is studied by using an improved least squares support vector machine （LSSVM） regression based on chaotic mutation evolutionary programming （CMEP） approach for parameter optimization. We analyze how the prediction error varies with different parameters （σ, γ） in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.
文摘We present a procedure that gives us an SOS (sum of squares) decomposition of a given real polynomial in variables, if there exists such decomposition. For the case of real polynomials in non-commutative variables we extend this procedure to obtain a sum of hermitian squares SOHS) decomposition whenever there exists any. This extended procedure is the main scientific contribution of the paper.
基金supported by the National Natural Science Foundation of China(61201282)the Science and Technology on Communication Information Security Control Laboratory Foundation(9140C130304120C13064)
文摘Time-differences-of-arrival （TDOA） and gain-ratios-of- arrival （GROA） measurements are used to determine the passive source location. Based on the measurement models, the con- strained weighted least squares （CWLS） estimator is presented. Due to the nonconvex nature of the CWLS problem, it is difficult to obtain its globally optimal solution. However, according to the semidefinite relaxation, the CWLS problem can be relaxed as a convex semidefinite programming problem （SDP）, which can be solved by using modern convex optimization algorithms. Moreover, this relaxation can be proved to be tight, i.e., the SDP solves the relaxed CWLS problem, and this hence guarantees the good per- formance of the proposed method. Furthermore, this method is extended to solve the localization problem with sensor position errors. Simulation results corroborate the theoretical results and the good performance of the proposed method.
文摘By attacking the linear programming problems from their dual side,a new general algorithm for linear programming is developed.At each iteration,the algorithm finds a feasible descent search direction by handling a least square problem associated with the dual system,using QR decomposition technique.The new method is a combination of pivot method and interior-point method.It in fact not only reduces the possibility of difficulty arising from degeneracy,but also has the same advantages as pivot method in warm-start to resolve linear programming problems.Numerical results of a group of randomly constructed problems are very encouraging.
基金Supported by the Science Foundation of Shaanxi Provincial Educational Department Natural Science Foundation of China（06JK152） Supported by the Graduate Innovation Project of Yanan uni- versity（YCX201003）
文摘The definition of generalized unified (C, α, ρ, d)-convex function is given. The concepts of generalized unified (C, α, ρ, d)-quasiconvexity, generalized unified (C, α, ρ, d)-pseudoconvexity and generalized unified (C, α, ρ, d)-strictly pseudoconvex functions are presented. The sufficient optimality conditions for multiobjective nonsmooth semi-infinite programming are obtained involving these generalized convexity lastly.
基金supported by the National Natural Science Foundation of China under Grant No.62101370。
文摘In the time-difference-of-arrival(TDOA)localization,robust least squares(LS)problems solved by mathematical programming were proven to be superior in mitigating the effects of non-line-of-sight(NLOS)propagation.However,the existing algorithms still suffer from two disadvantages:1)The algorithms strongly depend on prior information;2)The approaches do not satisfy the mean square error(MSE)optimal criterion of the measurement noise.To tackle the troubles,we first formulate an MSE minimization model for measurement noise by taking the source and the NLOS biases as variables.To obtain stable solutions,we introduce a penalty function to avoid abnormal estimates.We further tackle the nonconvex locating problem with semidefinite relaxation techniques.Finally,we incorporate mixed constraints and variable information to improve the estimation accuracy.Simulations and experiments show that the proposed method achieves consistent performance and good accuracy in dynamic NLOS environments.
