LMIs in Control/Observer Synthesis/Continuous Time/Reduced-Order State Observer
Reduced Order State Observer
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The Reduced Order State Observer design paradigm follows naturally from the design of Full Order State Observer.
The System
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The Data
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The matrices
A
,
B
,
C
,
D
{\displaystyle A,B,C,D}
are system matrices of appropriate dimensions and are known.
The Problem Formulation
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Given a State-space representation of a system given as above. First an arbitrary matrix
R
∈
R
(
n
−
m
)
x
n
{\displaystyle R\in \mathbb {R} ^{(n-m)xn}}
is chosen such that the vertical augmented matrix given as
T
=
[
C
R
]
{\displaystyle {\begin{aligned}T={\begin{bmatrix}C\\R\\\end{bmatrix}}\end{aligned}}}
is nonsingular, then
C
T
−
1
=
[
I
m
0
]
{\displaystyle {\begin{aligned}CT^{-1}={\begin{bmatrix}I_{m}&0\end{bmatrix}}\end{aligned}}}
Furthermore, let
T
A
T
−
1
=
[
A
11
A
12
A
21
A
22
]
,
A
11
∈
R
m
x
m
{\displaystyle {\begin{aligned}TAT^{-1}={\begin{bmatrix}A_{11}&A_{12}\\A_{21}&A_{22}\\\end{bmatrix}},A_{11}\in \mathbb {R} ^{mxm}\end{aligned}}}
then the matrix pair
(
A
22
,
A
12
)
{\displaystyle (A_{22},A_{12})}
is detectable if and only if
(
A
,
C
)
{\displaystyle (A,C)}
is detectable, then let
T
x
=
[
x
1
x
2
]
,
T
B
=
[
B
1
B
2
]
{\displaystyle {\begin{aligned}Tx={\begin{bmatrix}x_{1}\\x_{2}\\\end{bmatrix}},TB={\begin{bmatrix}B_{1}\\B_{2}\\\end{bmatrix}}\end{aligned}}}
then a new system of the form given below can be obtained
[
x
˙
1
x
˙
2
]
=
[
A
11
A
12
A
21
A
22
]
[
x
˙
1
x
˙
2
]
+
[
B
1
B
2
]
u
,
y
=
x
1
{\displaystyle {\begin{aligned}{\begin{bmatrix}{\dot {x}}_{1}\\{\dot {x}}_{2}\\\end{bmatrix}}={\begin{bmatrix}A_{11}&A_{12}\\A_{21}&A_{22}\\\end{bmatrix}}{\begin{bmatrix}{\dot {x}}_{1}\\{\dot {x}}_{2}\\\end{bmatrix}}+{\begin{bmatrix}B_{1}\\B_{2}\\\end{bmatrix}}u,y=x_{1}\end{aligned}}}
once an estimate of
x
2
{\displaystyle x_{2}}
is obtained the the full state estimate can be given as
x
^
=
T
−
1
[
y
x
^
2
]
{\displaystyle {\begin{aligned}{\hat {x}}=T^{-1}{\begin{bmatrix}y\\{\hat {x}}_{2}\\\end{bmatrix}}\end{aligned}}}
the the reduced order observer can be obtained in the form.
z
˙
=
F
z
+
G
y
+
H
u
,
x
^
2
=
M
z
+
N
y
{\displaystyle {\begin{aligned}{\dot {z}}&=Fz+Gy+Hu,\\{\hat {x}}_{2}&=Mz+Ny\\\end{aligned}}}
Such that for arbitrary control and arbitrary initial system values, There holds
l
i
m
t
→
∞
(
x
2
−
x
^
2
)
=
0
{\displaystyle {\begin{aligned}lim_{t\to \infty }(x_{2}-{\hat {x}}_{2})=0\end{aligned}}}
The value for
F
,
G
,
H
,
M
,
N
{\displaystyle F,G,H,M,N}
can be obtain by solving the following LMI.
The LMI:
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The reduced-order observer exists if and only if one of the two conditions holds.
1) There exist a symmetric positive definite Matrix
P
{\displaystyle P}
and a matrix
W
{\displaystyle W}
that satisfy
A
22
T
P
+
P
A
22
+
W
12
A
+
A
12
T
W
<
0.
{\displaystyle A_{22}^{T}P+PA_{22}+W_{12}^{A}+A_{12}^{T}W<0.}
Then
L
=
P
−
1
W
{\displaystyle L=P^{-1}W}
2) There exist a symmetric positive definite Matrix
P
{\displaystyle P}
that satisfies the below Matrix inequality
A
22
T
P
+
P
A
22
−
A
12
T
A
12
<
0
{\displaystyle A_{22}^{T}P+PA_{22}-A_{12}^{T}A_{12}<0}
Then
L
=
−
1
2
P
−
1
A
12
T
{\displaystyle L=-{\frac {1}{2}}P^{-1}A_{12}^{T}}
.
By using this value of
L
{\displaystyle L}
we can reconstruct the observer state matrices as
F
=
A
22
+
L
A
12
,
G
=
(
A
21
+
L
A
11
)
−
(
A
22
+
L
A
12
)
L
,
H
=
B
2
+
L
B
1
,
M
=
I
,
N
=
−
L
,
{\displaystyle {\begin{aligned}F=A_{22}+LA{12},G=(A_{21}+LA_{11})-(A_{22}+LA_{12})L,H=B_{2}+LB_{1},M=I,N=-L,\end{aligned}}}
Conclusion:
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Hence, we are able to form a reduced-order observer using which we can back of full state information as per the equation given at the end of the problem formulation given above.
External Links
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A list of references documenting and validating the LMI.
LMIs in Control Systems Analysis, Design and Applications - Duan and Yu
LMI Methods in Optimal and Robust Control - A course on LMIs in Control by Matthew Peet.
LMI Properties and Applications in Systems, Stability, and Control Theory - A List of LMIs by Ryan Caverly and James Forbes.
LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.
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