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An approximate-predictor approach to reduced-order models and controllers for distributed-parameter systems

机译:分布式参数系统降阶模型和控制器的近似预测器方法

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Two reduced-order digital controllers for distributed parameter systems (DPS) are described. Reduced-order models approximate the optimal finite past predictor and error covariance for the full system to minimize an approximation to the Kullback-Leibler information distance (KLID). An LQG controller based on a reduced-order-system model is described. A reduced-order controller is found to minimize the KLID between the closed-loop system outputs with the full- and reduced-order controllers. Noncollocated control of a flexible beam is simulated.
机译:描述了用于分布式参数系统(DPS)的两个降阶数字控制器。降阶模型使整个系统的最优有限过去预测因子和误差协方差近似,以最大程度地减小对Kullback-Leibler信息距离(KLID)的近似。描述了基于降阶系统模型的LQG控制器。发现使用降阶控制器可以最大程度地减少使用全阶和降阶控制器的闭环系统输出之间的KLID。模拟了柔性梁的非共置控制。

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