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{{Expert-subject|Mathematics|date=November 2008}} | |||
In [[control theory]], a '''Kalman decomposition''' provides a mathematical means to convert a representation of any [[LTI system theory|linear time-invariant]] [[control system]] to a form in which the system can be decomposed into a standard form which makes clear the [[Observability|observable]] and [[Controllability|controllable]] components of the system. This decomposition results in the system being presented with a more illuminating structure, making it easier to draw conclusions on the system's [[Reachability problem|reachable]] and observable subspaces. | |||
== Notation == | |||
The derivation is identical for both discrete-time as well as continuous time LTI systems. The description of a continuous time linear system is | |||
: <math>\dot{x}(t) = Ax(t) + Bu(t)</math> | |||
: <math>\, y(t) = Cx(t) + Du(t)</math> | |||
where | |||
: <math>\, x</math> is the "state vector", | |||
: <math>\, y</math> is the "output vector", | |||
: <math>\, u</math> is the "input (or control) vector", | |||
: <math>\, A</math> is the "state matrix", | |||
: <math>\, B</math> is the "input matrix", | |||
: <math>\, C</math> is the "output matrix", | |||
: <math>\, D</math> is the "feedthrough (or feedforward) matrix". | |||
Similarly, a discrete-time linear control system can be described as | |||
: <math>\, x(k+1) = Ax(k) + Bu(k)</math> | |||
: <math>\, y(k) = Cx(k) + Du(k)</math> | |||
with similar meanings for the variables. Thus, the system can be described using the tuple consisting of four matrices <math>\, (A, B, C, D)</math>. | |||
Let the order of the system be <math>\, n</math>. | |||
Then, the Kalman decomposition is defined as a transformation of the tuple <math>\, (A, B, C, D)</math> to <math>\, (\hat{A}, \hat{B}, \hat{C}, \hat{D})</math> as follows: | |||
: <math>\, {\hat{A}} = {T^{-1}}AT</math> | |||
: <math>\, {\hat{B}} = {T^{-1}}B</math> | |||
: <math>\, {\hat{C}} = CT</math> | |||
: <math>\, {\hat{D}} = D</math> | |||
<math>\, T</math> is an <math>\, n \times n</math> invertible matrix defined as | |||
: <math>\, T = \begin{bmatrix} T_{r\overline{o}} & T_{ro} & T_{\overline{ro}} & T_{\overline{r}o}\end{bmatrix}</math> | |||
where | |||
* <math>\, T_{r\overline{o}}</math> is a matrix whose columns span the subspace of states which are both reachable and unobservable. | |||
* <math>\, T_{ro}</math> is chosen so that the columns of <math>\, \begin{bmatrix} T_{r\overline{o}} & T_{ro}\end{bmatrix}</math> are a basis for the reachable subspace. | |||
* <math>\, T_{\overline{ro}}</math> is chosen so that the columns of <math>\, \begin{bmatrix} T_{r\overline{o}} & T_{\overline{ro}}\end{bmatrix}</math> are a basis for the unobservable subspace. | |||
* <math>\, T_{\overline{r}o}</math> is chosen so that <math>\,\begin{bmatrix} T_{r\overline{o}} & T_{ro} & T_{\overline{ro}} & T_{\overline{r}o}\end{bmatrix}</math> is invertible. | |||
By construction, the matrix <math>\, T</math> is invertible. It can be observed that some of these matrices may have dimension zero. For example, if the system is both observable and controllable, then <math>\, T = T_{ro}</math>, making the other matrices zero dimension. | |||
==Standard Form== | |||
By using results from controllability and observability, it can be shown that the transformed system <math>\, (\hat{A}, \hat{B}, \hat{C}, \hat{D})</math> has matrices in the following form: | |||
: <math>\, \hat{A} = \begin{bmatrix}A_{r\overline{o}} & A_{12} & A_{13} & A_{14} \\ | |||
0 & A_{ro} & 0 & A_{24} \\ | |||
0 & 0 & A_{\overline{ro}} & A_{34}\\ | |||
0 & 0 & 0 & A_{\overline{r}o}\end{bmatrix}</math> | |||
: <math>\, \hat{B} = \begin{bmatrix}B_{r\overline{o}} \\ B_{ro} \\ 0 \\ 0\end{bmatrix}</math> | |||
: <math>\, \hat{C} = \begin{bmatrix}0 & C_{ro} & 0 & C_{\overline{r}o}\end{bmatrix}</math> | |||
: <math>\, \hat{D} = D</math> | |||
This leads to the conclusion that | |||
* The subsystem <math>\, (A_{ro}, B_{ro}, C_{ro}, D)</math> is both reachable and observable. | |||
* The subsystem <math>\, \left(\begin{bmatrix}A_{r\overline{o}} & A_{12}\\ 0 & A_{ro}\end{bmatrix},\begin{bmatrix}B_{r\overline{o}} \\ B_{ro}\end{bmatrix},\begin{bmatrix}0 & C_{ro}\end{bmatrix}, D\right)</math> is reachable. | |||
* The subsystem <math>\, \left(\begin{bmatrix}A_{ro} & A_{24}\\ 0 & A_{\overline{r}o}\end{bmatrix},\begin{bmatrix}B_{ro} \\ 0 \end{bmatrix},\begin{bmatrix}C_{ro} & C_{\overline{r}o}\end{bmatrix}, D\right)</math> is observable. | |||
==See also== | |||
* [[Observability]] | |||
* [[Controllability]] | |||
==External links== | |||
*[http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-241j-dynamic-systems-and-control-spring-2011/readings/MIT6_241JS11_chap25.pdf Lectures on Dynamic Systems and Control, Lecture 25] - Mohammed Dahleh, Munther Dahleh, George Verghese — MIT OpenCourseWare | |||
[[Category:Control theory]] |
Latest revision as of 13:57, 23 November 2013
Template:Expert-subject In control theory, a Kalman decomposition provides a mathematical means to convert a representation of any linear time-invariant control system to a form in which the system can be decomposed into a standard form which makes clear the observable and controllable components of the system. This decomposition results in the system being presented with a more illuminating structure, making it easier to draw conclusions on the system's reachable and observable subspaces.
Notation
The derivation is identical for both discrete-time as well as continuous time LTI systems. The description of a continuous time linear system is
where
- is the "state vector",
- is the "output vector",
- is the "input (or control) vector",
- is the "state matrix",
- is the "input matrix",
- is the "output matrix",
- is the "feedthrough (or feedforward) matrix".
Similarly, a discrete-time linear control system can be described as
with similar meanings for the variables. Thus, the system can be described using the tuple consisting of four matrices . Let the order of the system be .
Then, the Kalman decomposition is defined as a transformation of the tuple to as follows:
is an invertible matrix defined as
where
- is a matrix whose columns span the subspace of states which are both reachable and unobservable.
- is chosen so that the columns of are a basis for the reachable subspace.
- is chosen so that the columns of are a basis for the unobservable subspace.
- is chosen so that is invertible.
By construction, the matrix is invertible. It can be observed that some of these matrices may have dimension zero. For example, if the system is both observable and controllable, then , making the other matrices zero dimension.
Standard Form
By using results from controllability and observability, it can be shown that the transformed system has matrices in the following form:
This leads to the conclusion that
- The subsystem is both reachable and observable.
- The subsystem is reachable.
- The subsystem is observable.
See also
External links
- Lectures on Dynamic Systems and Control, Lecture 25 - Mohammed Dahleh, Munther Dahleh, George Verghese — MIT OpenCourseWare