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Statistical process adjustment of multivariate processes with minimum control efforts

机译:通过最少的控制工作即可对多元过程进行统计过程调整

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In controlling a multiple-input-multiple-output (MIMO) process, usually all control variables have to be adjusted at each step, which may incur high adjustment cost. This paper proposes a Lasso adjustment algorithm, which minimizes the number of variables to be adjusted at each step. Simulation results show that the proposed algorithm can maintain acceptable output deviations while reduce the number of variables need to be adjusted significant.
机译:在控制多输入多输出(MIMO)过程中,通常必须在每个步骤中调整所有控制变量,这可能招致高昂的调整成本。本文提出了一种套索调整算法,该算法可将每个步骤要调整的变量数量减至最少。仿真结果表明,该算法可以保持可接受的输出偏差,同时减少需要大量调整的变量数量。

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