Then following the existing path-following method for solving BMI problem, an iterative LMI algorithm is proposed to locally search the desired output-feedback gain.
进一步，在问题有解时，通过极小化增益矩阵元素绝对值的和，给出了求解期望低成本输出反馈控制的算法。
Based on the model, the Taylor series coefficients of control function are adjusted by an iterative learning law and the learning gain matrix is designed via LMI optimization.
模型的基础上，泰勒级数的系数调整控制功能的迭代学习法律，学习增益矩阵，通过LMI优化设计。
Based on the model, the Taylor series coefficients of control function are adjusted by an iterative learning law and the learning gain matrix is designed via LMI optimization.
模型的基础上，泰勒级数的系数调整控制功能的迭代学习法律，学习增益矩阵，通过LMI优化设计。
应用推荐