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A '''weighting pattern''' for a [[linear dynamical system]] describes the relationship between an input <math>u</math> and output <math>y</math>Given the [[time-variant system]] described by
: <math>\dot{x}(t) = A(t)x(t) + B(t)u(t)</math>
: <math>y(t) = C(t)x(t)</math>
then the output can be written as
: <math>y(t) = y(t_0) + \int_{t_0}^t T(t,\sigma)u(\sigma) d\sigma</math>
where <math>T(\cdot,\cdot)</math> is the weighting pattern for the systemFor such a system the weighting pattern is <math>T(t,\sigma) = C(t)\phi(t,\sigma)B(\sigma)</math> such that <math>\phi</math> is the [[state transition matrix]].
 
The weighting pattern will determine a system, but note that if there exists a [[Realization (systems)|realization]] for this weighting pattern then there exists many that do so.<ref>{{cite book|first=Roger W.|last=Brockett|title=Finite Dimensional Linear Systems|publisher=John Wiley & Sons|year=1970|isbn=978-0-471-10585-5}}</ref>
 
==Linear time invariant system==
In a [[LTI system]] then the weighting pattern is:
; Continuous
: <math>T(t,\sigma) = C e^{A(t-\sigma)} B</math>
where <math>e^{A(t-\sigma)}</math> is the [[matrix exponential]].
 
; Discrete
: <math>T(k,l) = C A^{k-l-1} B</math>.
 
== References ==
{{Reflist}}
 
[[Category:Control theory]]

Latest revision as of 08:12, 23 January 2013

A weighting pattern for a linear dynamical system describes the relationship between an input and output . Given the time-variant system described by

then the output can be written as

where is the weighting pattern for the system. For such a system the weighting pattern is such that is the state transition matrix.

The weighting pattern will determine a system, but note that if there exists a realization for this weighting pattern then there exists many that do so.[1]

Linear time invariant system

In a LTI system then the weighting pattern is:

Continuous

where is the matrix exponential.

Discrete
.

References

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