本文首先借助hypergenic函数改进的柯西积分公式,呈现了hypergenic函数改进的柯西积分公式的另一种形式。接着,基于hypergenic函数与对偶的hypergenic函数两者之间的关系,我们推导出了对偶的hypergenic函数所对应的改进的柯西型积分公...本文首先借助hypergenic函数改进的柯西积分公式,呈现了hypergenic函数改进的柯西积分公式的另一种形式。接着,基于hypergenic函数与对偶的hypergenic函数两者之间的关系,我们推导出了对偶的hypergenic函数所对应的改进的柯西型积分公式。最后,进一步探讨并推导了关于(1 − n)-hypergenic函数的改进的积分表示。In this article, with the help of the hypergenic function for the improved Cauchy integral formula, we first give another form of the hypergenic function for the improved Cauchy integral formula. Then, on the basis of the relationship between hypergenic function and the dual hypergenic function, the dual hypergenic function for the improved Cauchy integral formula is obtained. Finally, the related results of a (1 − n)-hypergenic function for the improved integral representation are derived.展开更多
本文用连续可微非凸函数描述的概率约束分析非线性随机优化问题。为此描述了潜在概率函数的水平集的切锥和法锥,并在此基础上,提出p-有效点的定义,形成问题的一阶和二阶最优性条件,基于p-有效点生成的概率函数的水平集,通过修正的Carrol...本文用连续可微非凸函数描述的概率约束分析非线性随机优化问题。为此描述了潜在概率函数的水平集的切锥和法锥,并在此基础上,提出p-有效点的定义,形成问题的一阶和二阶最优性条件,基于p-有效点生成的概率函数的水平集,通过修正的Carroll函数生成一个对偶算法。In this paper, probabilistic constraints described by continuously differentiable non-convex functions are used to analyze nonlinear stochastic optimization problems. To this end, the tangent and normal cones of the level set of potential probability functions are described, and on this basis, the definition of p-effective points is proposed to form the first and second order optimality conditions of the problem. Based on the water-level set of probability functions generated by p-effective points, a dual algorithm is generated by the modified Carroll function.展开更多
本文通过连续可微的非凸函数所形成的概率约束,来分析概率约束问题。描述了潜在的概率函数的水平集的切锥和法锥。进一步,基于p-有效点的概念,形成这些问题的一阶和二阶最优性条件。对于离散分布函数的这种情况,产生一个基于修正的指数...本文通过连续可微的非凸函数所形成的概率约束,来分析概率约束问题。描述了潜在的概率函数的水平集的切锥和法锥。进一步,基于p-有效点的概念,形成这些问题的一阶和二阶最优性条件。对于离散分布函数的这种情况,产生一个基于修正的指数函数的对偶算法来解决概率约束问题。In this paper, the problem of probability constraints is analyzed by means of the probability constraints formed by continuously differentiable non-convex functions. The tangent and normal cones of the level set of potential probability functions are described. Further, based on the concept of p-efficient points, the first and second order optimality conditions of these problems are formed. For this case of the discrete distribution function, a dual algorithm based on the modified exponential function is generated to solve the probability constraint problem.展开更多
针对未知参数系统的自适应预测函数控制,模型尚未辨识完成或外界干扰造成的模型不准确,会严重影响控制效果,并产生较大的超调和波动,由此,提出一类对偶自适应预测函数控制(Dual Adaptive Predictive Function Control,DAPFC)算法。在模...针对未知参数系统的自适应预测函数控制,模型尚未辨识完成或外界干扰造成的模型不准确,会严重影响控制效果,并产生较大的超调和波动,由此,提出一类对偶自适应预测函数控制(Dual Adaptive Predictive Function Control,DAPFC)算法。在模型辨识的过程中,通过辨识误差的大小,利用对偶控制方法来调整原有自适应控制律,尽可能地获取未知参数信息并抑制由于模型失配造成的控制量的波动。改善了系统在模型失配时的控制效果,并具有较强的鲁棒性。仿真结果表明,该算法具有良好的控制品质。展开更多
文摘本文首先借助hypergenic函数改进的柯西积分公式,呈现了hypergenic函数改进的柯西积分公式的另一种形式。接着,基于hypergenic函数与对偶的hypergenic函数两者之间的关系,我们推导出了对偶的hypergenic函数所对应的改进的柯西型积分公式。最后,进一步探讨并推导了关于(1 − n)-hypergenic函数的改进的积分表示。In this article, with the help of the hypergenic function for the improved Cauchy integral formula, we first give another form of the hypergenic function for the improved Cauchy integral formula. Then, on the basis of the relationship between hypergenic function and the dual hypergenic function, the dual hypergenic function for the improved Cauchy integral formula is obtained. Finally, the related results of a (1 − n)-hypergenic function for the improved integral representation are derived.
文摘本文用连续可微非凸函数描述的概率约束分析非线性随机优化问题。为此描述了潜在概率函数的水平集的切锥和法锥,并在此基础上,提出p-有效点的定义,形成问题的一阶和二阶最优性条件,基于p-有效点生成的概率函数的水平集,通过修正的Carroll函数生成一个对偶算法。In this paper, probabilistic constraints described by continuously differentiable non-convex functions are used to analyze nonlinear stochastic optimization problems. To this end, the tangent and normal cones of the level set of potential probability functions are described, and on this basis, the definition of p-effective points is proposed to form the first and second order optimality conditions of the problem. Based on the water-level set of probability functions generated by p-effective points, a dual algorithm is generated by the modified Carroll function.
文摘本文通过连续可微的非凸函数所形成的概率约束,来分析概率约束问题。描述了潜在的概率函数的水平集的切锥和法锥。进一步,基于p-有效点的概念,形成这些问题的一阶和二阶最优性条件。对于离散分布函数的这种情况,产生一个基于修正的指数函数的对偶算法来解决概率约束问题。In this paper, the problem of probability constraints is analyzed by means of the probability constraints formed by continuously differentiable non-convex functions. The tangent and normal cones of the level set of potential probability functions are described. Further, based on the concept of p-efficient points, the first and second order optimality conditions of these problems are formed. For this case of the discrete distribution function, a dual algorithm based on the modified exponential function is generated to solve the probability constraint problem.
文摘针对未知参数系统的自适应预测函数控制,模型尚未辨识完成或外界干扰造成的模型不准确,会严重影响控制效果,并产生较大的超调和波动,由此,提出一类对偶自适应预测函数控制(Dual Adaptive Predictive Function Control,DAPFC)算法。在模型辨识的过程中,通过辨识误差的大小,利用对偶控制方法来调整原有自适应控制律,尽可能地获取未知参数信息并抑制由于模型失配造成的控制量的波动。改善了系统在模型失配时的控制效果,并具有较强的鲁棒性。仿真结果表明,该算法具有良好的控制品质。
