基于Schur收敛性条件的扰动特征泛函凸组合模型

Turbulence Characteristics Functional Convex Combination Model Based on Schur Convergence Condition

研究Schur收敛性条件的扰动特征泛函凸组合模型的收敛性和稳定性,是实现对特征灵敏的前馈网络系统连续性和非线性控制的关键理论依据。传统分析方法采用的模糊免疫时滞环节进行完全跟踪补偿,构造李雅普诺夫泛函线性矩阵不等式,进行非线性凸组合模型构建,但模型因扰动特征泛函收敛效果不好。构建了基于Schur收敛性条件的扰动特征泛函凸组合模型,求解平均扰动特征泛函的平均互信息量,设定扰动特征连接权值下的系统函数,通过实时自适应学习算法对被控对象进行亏损特征分解,得到Schur收敛性条件,对凸组合模型的收敛性和渐进稳定性进行证明。最后进行数值算例分析,得出构建的凸组合模型收敛性和渐进稳定性较好,计算精度精确,寻优过程可靠。

The condition of Schur convergence of the perturbation characteristic functional convex combination model convergence and stability is researched, it is to achieve the characteristics of sensitive feed forward control network system continuity and nonlinear critical theory. Fuzzy immune time delay is used in the traditional analysis method with full compensation, Lyapunov functional linear matrix inequality is constructed, the nonlinear convex combination model is obtained, but the model due to disturbances of functional, convergence effect is not good. Construction of the disturbance characteristic functional convex combination model of Schur based on the average convergence conditions is obtained, calculate the average disturbance characteristic functional mutual information, The disturbance characteristics connection system function weights is set, the adaptive learning algorithm is used for eigenvalue decomposition, the Schur convergence condition is obtained, the convergence and asymptotic stability property of convex combination model is proved. Finally, a numerical example analysis is taken, it concludes that the construction of the convex has better convergence and asymptotic stability,the calculation accuracy is improved, and the optimization process is reliable.