Titlebook: Control Configuration Selection for Multivariable Plants; Ali Khaki-Sedigh,Bijan Moaveni Book 2009 Springer-Verlag Berlin Heidelberg 2009

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Control Configuration Selection of Linear Multivariable Plants Based on the State-Space Models, steady state transfer function matrix, and the advanced pairing methods based on the RGA concept or the passivity approach use the dynamic transfer function matrix. In this chapter, input-output pairing methods based on the dynamical state-space model of the plant are introduced. State space is an

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Control Configuration Selection of Linear Uncertain Multivariable Plants,riable plants, the control configuration of the plant may endure fundamental changes, which will severely degrade the decentralized controller performance. The well-known input-output pairing techniques described in previous sections are unable to analyze the effect of uncertainty on input-output pa

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Book 2009esign methodologies for multivariable plants can be categorized as centralized and decentralized design strategies. Despite the remarkable theoretical achievements in centralized multiva- able control, decentralized control is still widely used in many industrial plants. This trend in the beginning

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Aspekte der Kreuz- bzw. Gruppenallergiection 4.3. This strategy employs the passivity concept. Although the properties and applications of passivity theory are well known in stability analysis and control systems design, it has been newly introduced in interaction analysis and it uses the so-called ..

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https://doi.org/10.1007/978-3-642-82630-6 The materials of this chapter are based on (Daoutidis and Kravaris 1992), (Glad 1999) and (Moaveni and Khaki-Sedigh 2007) and covers the class of affine nonlinear multivariable plants. Worked examples and simulation results are provided to show the effectiveness of the nonlinear pairing methodologies, and limitations of the classical RGA.

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