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多时间尺度问题在控制领域已得到广泛关注。针对多时间尺度问题的典型代表——双时间尺度问题,学者们已提出多种控制算法来分析处理。这些控制算法大多是根据奇异摄动法将控制系统分解为快、慢两个独立的子系统,并对子系统分别进行优化求解,这类算法往往忽略子系统之间控制与输出的耦合作用。本文在上述控制算法的基础上,提出一种考虑快、慢子系统双方控制与输出间的耦合作用的双时间尺度预测控制算法。该算法以系统原状态空间模型分解得到的快、慢两个子系统模型为被控对象,将两个模型的预测值信息整合到同一预测控制优化问题中,实现对整个系统的控制。仿真实例验证了该方法的有效性。
Multi-time scale problems have received extensive attention in the field of control. For the typical representative of multi-time scale problem-double time scale problem, scholars have proposed a variety of control algorithms to analyze and process. Most of these control algorithms decompose the control system into fast and slow subsystems based on the singular perturbation method and optimize the subsystems separately. Such algorithms tend to neglect the coupling between the control and output of the subsystems. Based on the above control algorithm, this paper proposes a dual-time-scale predictive control algorithm that considers the coupling between control and output of both fast and slow subsystems. The algorithm takes both fast and slow subsystem models decomposed into the original state space model as controlled objects and integrates the predictive value information of the two models into the same predictive control optimization problem to realize the control of the entire system. Simulation results show the effectiveness of the method.