Abstract
Several researches have formulated economic performance optimization problems taking account of a trade-off relation between process input and output variance. The present work introduces theoretical formulations that relate the weighting parameter with each input and output variance on the condition that the Linear Quadratic Gaussian (LQG) controllers are implemented as lower layer controllers. The proposed approach is applied to a two-input, two-output separation process model, and solves optimal weighting parameter based on LQG control. The numerical example also shows that the obtained optimal weighting parameter is effective for a MPC based learning algorithm.
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