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Robust
H
2
{\displaystyle H_{2}}
State Feedback Control [ edit | edit source ]
For the uncertain linear system given below, and a scalar
γ
>
0
{\displaystyle \gamma >0}
. The goal is to design a state feedback control
u
(
t
)
{\displaystyle u(t)}
in the form of
u
(
t
)
=
K
x
(
t
)
{\displaystyle u(t)=Kx(t)}
such that the closed-loop system is asymptotically stable and satisfies.
|
|
G
z
w
(
s
)
|
|
2
<
γ
{\displaystyle {\begin{aligned}||G_{zw}(s)||_{2}<\gamma \end{aligned}}}
Consider System with following state-space representation.
x
˙
(
t
)
=
(
A
+
Δ
A
)
x
(
t
)
+
(
B
1
+
Δ
B
1
)
u
(
t
)
+
B
2
w
(
t
)
z
(
t
)
=
C
x
(
t
)
+
D
1
u
(
t
)
+
D
2
w
(
t
)
{\displaystyle {\begin{aligned}{\dot {x}}(t)&=(A+\Delta {A})x(t)+(B_{1}+\Delta {B_{1}})u(t)+B_{2}w(t)\\z(t)&=Cx(t)+D_{1}u(t)+D_{2}w(t)\\\end{aligned}}}
where
x
∈
R
n
{\displaystyle x\in \mathbb {R} ^{n}}
,
u
∈
R
r
{\displaystyle u\in \mathbb {R} ^{r}}
,
w
∈
R
p
{\displaystyle w\in \mathbb {R} ^{p}}
,
z
∈
R
m
{\displaystyle z\in \mathbb {R} ^{m}}
.
For
H
2
{\displaystyle H_{2}}
state feedback control
D
2
=
0
{\displaystyle D_{2}=0}
Δ
A
{\displaystyle \Delta {A}}
and
Δ
B
1
{\displaystyle \Delta {B_{1}}}
are real valued matrix functions that represent the time varying parameter uncertainties and of the form
[
Δ
A
Δ
B
1
]
=
H
F
[
E
1
E
2
]
{\displaystyle {\begin{aligned}{\begin{bmatrix}\Delta {A}&\Delta {B_{1}}\end{bmatrix}}=HF{\begin{bmatrix}E_{1}&E_{2}\end{bmatrix}}\end{aligned}}}
where matrices
E
1
,
E
2
{\displaystyle E_{1},E_{2}}
and
H
{\displaystyle H}
are some known matrices of appropriate dimensions, while
F
{\displaystyle F}
is a matrix which contains the uncertain parameters and satisfies.
F
T
F
≤
I
{\displaystyle {\begin{aligned}F^{T}F\leq I\end{aligned}}}
For the perturbation, we obviously have
[
Δ
A
Δ
B
1
]
=
[
0
0
]
{\displaystyle {\begin{aligned}{\begin{bmatrix}\Delta {A}&\Delta {B_{1}}\end{bmatrix}}={\begin{bmatrix}0&0\end{bmatrix}}\end{aligned}}}
, for
F
=
0
{\displaystyle F=0}
[
Δ
A
Δ
B
1
]
=
H
[
E
1
E
2
]
{\displaystyle {\begin{aligned}{\begin{bmatrix}\Delta {A}&\Delta {B_{1}}\end{bmatrix}}=H{\begin{bmatrix}E_{1}&E_{2}\end{bmatrix}}\end{aligned}}}
, for
F
=
0
{\displaystyle F=0}
The
H
2
{\displaystyle H_{2}}
state feedback control problem has a solution if and only if there exist a scalar
β
{\displaystyle \beta }
, a matrix
W
{\displaystyle W}
, two symmetric matrices
Z
{\displaystyle Z}
and
X
{\displaystyle X}
satisfying the following LMI's problem.
min
γ
2
::
{\displaystyle \min \gamma ^{2}::}
[
⟨
A
X
+
B
1
W
⟩
s
+
B
2
B
2
T
+
β
H
H
(
T
)
(
E
1
X
+
E
2
W
)
T
E
1
X
+
E
2
W
−
β
I
]
<
0
{\displaystyle {\begin{aligned}{\begin{bmatrix}\langle AX+B_{1}W\rangle _{s}+B_{2}B_{2}^{T}+\beta {H}H^{(}T)&(E_{1}X+E_{2}W)^{T}\\E_{1}X+E_{2}W&-\beta {I}\end{bmatrix}}<0\end{aligned}}}
[
−
Z
C
X
+
D
1
W
(
C
X
+
D
1
W
)
T
−
X
]
<
0
{\displaystyle {\begin{aligned}{\begin{bmatrix}-Z&CX+D_{1}W\\(CX+D_{1}W)^{T}&-X\end{bmatrix}}<0\end{aligned}}}
t
r
a
c
e
(
Z
)
<
γ
2
{\displaystyle {\begin{aligned}trace(Z)<\gamma ^{2}\end{aligned}}}
where
⟨
M
⟩
s
=
(
M
+
M
T
)
{\displaystyle \langle M\rangle _{s}=(M+M^{T})}
is the definition that is need for the above LMI.
In this case, an
H
2
{\displaystyle H_{2}}
state feedback control law is given by
u
(
t
)
=
W
X
−
1
x
(
t
)
{\displaystyle u(t)=WX^{-1}x(t)}
.
LMIs in Control Systems Analysis, Design and Applications - Duan and Yu
A course on LMIs in Control by Matthew Peet.
LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.