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Continuous-time Generalized Predictive Control based on Poisson-Laguerre models

机译:基于Poisson-Laguerre模型的连续时间广义预测控制

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A Generalized Continuous-time Predictive Control (CGPC) based on Poisson-Laguerre (PL) models is proposed and analyzed. The output signal predictor is obtained without truncating the McLaurin series and then no output predictor order (Ny) is needed. The used matrices integrals in the CGPC algorithm could be computed analytically. Conditions on control parameters to guarantee the stability of the closed loop are given and discussed. For this kind of models, with a non-zero control-weighting parameter the disturbances elimination is not guaranteed. This problem have been diverted by proposing another way to compute the command signal.
机译:提出并分析了基于Poisson-Laguerre(PL)模型的广义连续时间预测控制(CGPC)。无需截断McLaurin系列即可获得输出信号预测变量,因此不需要输出预测变量阶数(Ny)。可以对CGPC算法中使用的矩阵积分进行解析计算。给出并讨论了控制参数的条件,以确保闭环的稳定性。对于这种模型,如果控制权重参数为非零,则无法保证消除干扰。通过提出另一种计算命令信号的方法,该问题已被转移。

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