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A novel centralized controller design method is proposed for multivariablesystems, whether square or nonsquare processes. First, the relationshipbetween equivalent transfer function (ETF) and the pseudo-inverseof multivariable transfer matrix is derived. Second, the relativenormalized gain array (RNGA)-based ETF parametrization method is extendedto the nonsquare processes. Finally, a centralized proportional integral/proportionalintegral derivative (PI/PID) multivariable controller is obtainedfrom the Maclaurin expansion. The effectiveness of the proposed approachis verified by analysis of several multivariable industrial processes;better overall performance is demonstrated compared with other centralizedcontrol methods. [ABSTRACT FROM AUTHOR]

Inthis paper, a novel decoupling control scheme based on adjoint matrixis proposed. By introducing the concept of characteristic sequence,the characteristic sequence of both the adjoint transfer matrix andthe determinant transfer function are derived from that of originalprocess transfer matrix. The adjoint transfer matrix and determinanttransfer function are then determined. Finally, the adjoint matrixis selected as a decoupler, and the decentralized controller is designedfor the determinant transfer function. The effectiveness of the proposeddesign approach is verified by three multivariable industrial processes,which shows that it results in better overall performance comparedwith other methods. [ABSTRACT FROM AUTHOR]

Time-varying fault characteristics have not yet beenaddressedby conventional fault-reconstruction-based modeling methods, whichcould affect fault diagnosis performance. In the present work, themultiple-time-region (MTR) nature, that is, the multiplicity of faultcharacteristics along with the process evolution, is proposed andefficiently analyzed for fault diagnosis. First, an automatic time-region-divisionalgorithm is developed that can partition the whole fault processinto different local regions according to the changes in fault characteristics.Different local fault characteristics are thus analyzed by buildingdifferent representative fault feature models in multiple time regions.Following the changing relationships between the fault and normaloperation statuses, different fault reconstruction actions are finallytaken in different time regions. By a proper time-region division,the proposed method can better model the time-varying fault behaviorsand capture the different fault-to-normal reconstruction relationshipsfor fault diagnosis. The feasibility and performance of the proposedmethod are illustrated with the Tennessee Eastman process, revealingenhanced fault understanding and improved fault diagnosis performance. [ABSTRACT FROM AUTHOR]