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本文将序列模型逼近法推广到稳态大系统的递阶优化与控制中去。文中采用拉格朗日乘子技术使问题得以分解;同时给出推广的算法在单迭代和双迭代策略下的公式推导,并用数值例题对两种迭代策略以及推广的算法与修正两步法进行比较。仿真结果表明:本文提出的推广算法比以前的修正两步法收敛速度快,数值稳定性好。
In this paper, we generalize the sequence model approximation to the hierarchical optimization and control of large-scale steady state systems. In this paper, the Lagrange multiplier technique is used to decompose the problem. At the same time, the formulaic deduction of the generalized algorithm under single-iteration and double-iterative strategy is given. Two iterative strategies and two-step generalized algorithm Compare The simulation results show that the proposed algorithm proposed in this paper has faster convergence rate and better numerical stability than the previous two-step modified method.