2003
DOI: 10.1109/tac.2003.816062
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Selection of variables for stabilizing control using pole vectors

Abstract: For a linear multivariable plant, it is known from earlier work that the easy computable pole vectors provide useful information about in which input channel (actuator) a given mode is controllable and in which output channel (sensor) it is observable. In this paper we provide a rigorous theoretical basis for the use of pole vectors, by providing a link to previous results on performance limitations for unstable plants.

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Cited by 11 publications
(14 citation statements)
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References 15 publications
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“…Clearly, the achievable input performance is zero for stable systems. These results generalize the previous results of Havre and Skogestad [4] to systems with multiple unstable poles and time delay.…”
Section: Introductionsupporting
confidence: 90%
See 1 more Smart Citation
“…Clearly, the achievable input performance is zero for stable systems. These results generalize the previous results of Havre and Skogestad [4] to systems with multiple unstable poles and time delay.…”
Section: Introductionsupporting
confidence: 90%
“…However, the focus has largely been on obtaining bounds on sensitivity and complementary sensitivity functions. Havre and Skogestad derived expressions for lower bound on achievable input performance for unstable systems [3] and extended their results to get exact expressions for rational systems with single unstable pole [4]. Chen et.…”
Section: Introductionmentioning
confidence: 99%
“…The output pole vector y p,i for a process with statespace representation (A, B, C, D) is defined by (Havre and Skogestad (2003))…”
Section: Pole Vectorsmentioning
confidence: 99%
“…being Q a positive definite matrix. A similar idea was firstly introduced in Havre and Skogestad (2003), but for optimal feedback stabilization of a system with only one unstable pole. The dependence of the index (11) with the chosen pattern is very complex, but it is possible to compare them, at least, in a numerical way.…”
Section: Minimization Of a Cost Indexmentioning
confidence: 99%