论文标题
双线性控制系统的时间和频率有限的H2-最佳模型订单减少
Time- and frequency-limited H2-optimal model order reduction of bilinear control systems
论文作者
论文摘要
在时间和频率限制的模型降低中，寻求原始高阶模型的减少顺序近似，以确保在某些所需的时间和频率间隔内确保卓越的准确性。我们首先考虑双线性控制系统的时间限制的H2-最佳模型降低降低问题，并得出一阶最佳条件，局部最佳减小阶模型应满足。然后，我们提出了一种启发式算法，该算法会生成降级模型，该算法倾向于达到这些最佳条件。还考虑了频率限制和时间限制的H2-pseudo-最佳模型还原问题，其中我们将重点放在构建降低的模型上，该模型满足局部最佳最佳条件的各个最佳条件的子集。已经提出了两种新的算法，该算法在收敛时降低的模型上的四个最佳条件中强制执行两个算法。对算法进行了三个数值示例测试，以验证本文中介绍的理论结果。数值结果证实了所提出的算法的功效。
In the time- and frequency-limited model order reduction, a reduced-order approximation of the original high-order model is sought to ensure superior accuracy in some desired time and frequency intervals. We first consider the time-limited H2-optimal model order reduction problem for bilinear control systems and derive first-order optimality conditions that a local optimum reduced-order model should satisfy. We then propose a heuristic algorithm that generates a reduced-order model, which tends to achieve these optimality conditions. The frequency-limited and the time-limited H2-pseudo-optimal model reduction problems are also considered wherein we restrict our focus on constructing a reduced-order model that satisfies a subset of the respective optimality conditions for the local optimum. Two new algorithms have been proposed that enforce two out of four optimality conditions on the reduced-order model upon convergence. The algorithms are tested on three numerical examples to validate the theoretical results presented in the paper. The numerical results confirm the efficacy of the proposed algorithms.
