This tutorial example shows how to specify LMI systems at the command line using the LMI Lab tools.
Consider a stable transfer function,
Suppose that G has four inputs, four outputs, and six states. Consider also a set of input/output scaling matrices D with block-diagonal structure given by:
The following problem arises in the robust stability analysis of systems with time-varying uncertainty [4]. Find, if any, a scaling D with the specified structure, such that the largest gain across frequency of is less than 1.
This problem has a simple LMI formulation: There exists an adequate scaling D if the following feasibility problem has solutions. Find two symmetric matrices and such that:
You can use the LMI Editor to specify the LMI problem described by these expressions, as shown in Specify LMIs with the LMI Editor GUI. Alternatively, define it at the command line using lmivar
and lmiterm
, as follows.
For this example, use the following values for A, B, and C.
A = [ -0.8715 0.5202 0.7474 1.0778 -0.9686 0.1005; -0.5577 -1.0843 1.8912 0.2523 1.0641 -0.0345; -0.2615 -1.7539 -1.5452 -0.2143 0.0923 -2.4192; 0.6087 -1.0741 0.1306 -2.5575 2.3213 0.2388; -0.7169 0.3582 -1.4195 1.7043 -2.6530 -1.4276; -1.2944 -0.6752 1.6983 1.6764 -0.3646 -1.7730 ]; B = [ 0 0.8998 -0.2130 0.9835; 0 -0.3001 0 -0.2977; -1.0322 0 -1.0431 1.1437; 0 -0.3451 -0.2701 -0.5316; -0.4189 1.0128 -0.4381 0; 0 0 -0.4087 0]; C = [ 0 2.0034 0 1.0289 0.1554 0.7135; 0.9707 0.9510 0.7059 1.4580 -1.2371 0.3174; 0 0 1.4158 0.0475 -2.1935 0.4136; -0.4383 0.6489 -1.6045 1.7463 -0.3334 -0.5771];
Define the LMI variables X
and S
, and then specify the terms of each LMI.
setlmis([]) X = lmivar(1,[6 1]); S = lmivar(1,[2 0;2 1]); % 1st LMI lmiterm([1 1 1 X],1,A,'s'); lmiterm([1 1 1 S],C',C); lmiterm([1 1 2 X],1,B); lmiterm([1 2 2 S],-1,1); % 2nd LMI lmiterm([-2 1 1 X],1,1); % 3rd LMI lmiterm([-3 1 1 S],1,1); lmiterm([3 1 1 0],1); LMISYS = getlmis;
The lmivar
commands define the two matrix variables, X and S. The lmiterm
commands describe the terms in each LMI. getlmis
returns the internal representation LMISYS
of this LMI problem.
For more details on how to use these commands, see:
For more information about how lmivar
updates the internal representation of the LMI problem, see How lmivar and lmiterm Manage LMI Representation.
The description of an LMI system should begin with setlmis
and end with getlmis
. The function setlmis
initializes the LMI system description.
When specifying a new system, type
setlmis([])
To add on to an existing LMI system with internal representation LMIS0
,
type
setlmis(LMIS0)
The matrix variables are declared one at a time with lmivar
and are characterized by their
structure. To facilitate the specification of this structure, the
LMI Lab offers two predefined structure types along with the means
to describe more general structures:
Type 1 | Symmetric block diagonal structure. This corresponds to matrix variables of the form $$X=\left(\begin{array}{cccc}{D}_{1}& 0& \dots & 0\\ 0& {D}_{2}& \ddots & \vdots \\ \vdots & \ddots & \ddots & 0\\ 0& \dots & 0& {D}_{r}\end{array}\right)$$ where each diagonal block D_{j} is square and is either zero, a full symmetric matrix, or a scalar matrix D_{j}= d × I, d ∊ R This type encompasses ordinary symmetric matrices (single block) and scalar variables (one block of size one). |
Type 2 | Rectangular structure. This corresponds to arbitrary rectangular matrices without any particular structure. |
Type 3 | General structures.
This third type is used to describe more sophisticated structures
and/or correlations between the matrix variables. The principle is
as follows: each entry of X is specified independently
as either 0, xn, or –xn
where xn denotes the n-th
decision variable in the problem. For details on how to use Type 3,
see Structured Matrix Variables as well as the |
In Specify LMI System, the matrix variables X and S are of Type 1. Indeed, both are symmetric and S inherits the block-diagonal structure of D. Specifically, S is of the form
$$S=\left(\begin{array}{cccc}{s}_{1}& 0& 0& 0\\ 0& {s}_{1}& 0& 0\\ 0& 0& {s}_{2}& {s}_{3}\\ 0& 0& {s}_{3}& {s}_{4}\end{array}\right).$$
Initialize the description and declare these two matrix variables.
setlmis([]) lmivar(1,[6 1]); % X lmivar(1,[2 0;2 1]); % S
In both lmivar
commands, the first input
specifies the structure type and the second input contains additional
information about the structure of the variable:
For a matrix variable X of Type 1, this second input is a matrix with two columns and as many rows as diagonal blocks in X. The first column lists the sizes of the diagonal blocks and the second column specifies their nature with the following convention:
1: full symmetric block
0: scalar block
–1: zero block
In the second command, for instance,[2 0;2 1]
means
that S has two diagonal blocks, the first one
being a 2-by-2 scalar block and the second one a 2-by-2 full block.
For matrix variables of Type 2, the second input of lmivar
is a two-entry vector listing
the row and column dimensions of the variable. For instance, a 3-by-5
rectangular matrix variable would be defined by
lmivar(2,[3 5])
For convenience, lmivar
also
returns a "tag" that identifies the matrix variable
for subsequent reference. For instance, X and S in Specify LMI System could be
defined by
X = lmivar(1,[6 1]); S = lmivar(1,[2 0;2 1]);
The identifiers X and S are
integers corresponding to the ranking of X and S in
the list of matrix variables (in the order of declaration). Here their
values would be X=1
and S=2
.
Note that these identifiers still point to X and S after
deletion or instantiation of some of the matrix variables. Finally, lmivar
can also return the total number
of decision variables allocated so far as well as the entry-wise dependence
of the matrix variable on these decision variables (see the lmivar
entry in the reference pages for
more details).
After declaring the matrix variables with lmivar
, we are left with specifying the
term content of each LMI. Recall that LMI terms fall into three categories:
The constant terms, i.e., fixed matrices like I in the left side of the LMI S > I.
The variable terms, i.e., terms involving a matrix variable. For instance, A^{T}X and C^{T}SC in the expression:
$$\left(\begin{array}{cc}{A}^{T}X+XA+{C}^{T}SC& XB\\ {B}^{T}X& -S\end{array}\right)<0$$
Variable terms are of the form PXQ where X is a variable and P, Q are given matrices called the left and right coefficients, respectively.
The outer factors.
When describing the term content of an LMI, specify only the terms in the blocks on or above the diagonal. The inner factors being symmetric, this is sufficient to specify the entire LMI. Specifying all blocks results in the duplication of off-diagonal terms, hence in the creation of a different LMI. Alternatively, you can describe the blocks on or below the diagonal.
LMI terms are specified one at a time with lmiterm
. For instance, the LMI
$$\left(\begin{array}{cc}{A}^{T}X+XA+{C}^{T}SC& XB\\ {B}^{T}X& -S\end{array}\right)<0$$
is described by
lmiterm([1 1 1 1],1,A,'s');
lmiterm([1 1 1 2],C',C);
lmiterm([1 1 2 1],1,B);
lmiterm([1 2 2 2],-1,1);
These commands successively declare the terms A^{T}X + XA, C^{T}SC, XB, and –S. In each command, the first argument is a four-entry vector listing the term characteristics as follows:
The first entry indicates to which LMI the term belongs.
The value m
means "left side of the m-th
LMI," and −m
means "right
side of the m-th LMI."
The second and third entries identify the block to
which the term belongs. For instance, the vector [1 1 2 1
]
indicates that the term is attached to the (1, 2) block.
The last entry indicates which matrix variable is
involved in the term. This entry is 0
for constant
terms, k
for terms involving the k-th
matrix variable X_{k},
and −k
for terms involving $${X}_{k}^{T}$$ (here X and S are
first and second variables in the order of declaration).
Finally, the second and third arguments of lmiterm
contain the numerical data (values
of the constant term, outer factor, or matrix coefficients P and Q for
variable terms PXQ or PX^{T}Q).
These arguments must refer to existing MATLAB^{®} variables and be real-valued.
See Complex-Valued LMIs for the specification of LMIs with complex-valued
coefficients.
Some shorthand is provided to simplify term specification. First,
blocks are zero by default. Second, in diagonal blocks the
extra argument 's'
allows you to specify the conjugated
expression AXB + B^{T}X^{T}A^{T} with
a single lmiterm
command.
For instance, the first command specifies A^{T}X + XA as
the "symmetrization" of XA. Finally,
scalar values are allowed as shorthand for scalar matrices,
i.e., matrices of the form αI with α
scalar. Thus, a constant term of the form αI can
be specified as the "scalar" α. This also applies
to the coefficients P and Q of
variable terms. The dimensions of scalar matrices are inferred from
the context and set to 1 by default. For instance, the third LMI S > I in Specify Matrix Variable Structures is described
by
lmiterm([-3 1 1 2],1,1); % 1*S*1 = S lmiterm([3 1 1 0],1); % 1*I = I
Recall that by convention S
is considered
as the right side of the inequality, which justifies the –3
in the first command.
Finally, to improve readability it is often convenient to attach
an identifier (tag) to each LMI and matrix variable. The variable
identifiers are returned by lmivar
and
the LMI identifiers are set by the function newlmi
.
These identifiers can be used in lmiterm
commands
to refer to a given LMI or matrix variable. For the LMI system of Specify LMI System, this would
look like:
setlmis([])
X = lmivar(1,[6 1]);
S = lmivar(1,[2 0;2 1]);
BRL = newlmi;
lmiterm([BRL 1 1 X],1,A,'s');
lmiterm([BRL 1 1 S],C',C);
lmiterm([BRL 1 2 X],1,B);
lmiterm([BRL 2 2 S],-1,1);
Xpos = newlmi;
lmiterm([-Xpos 1 1 X],1,1);
Slmi = newlmi;
lmiterm([-Slmi 1 1 S],1,1);
lmiterm([Slmi 1 1 0],1);
When the LMI system is completely specified, get the internal representation of the problem.
LMISYS = getlmis;
This returns the internal representation LMISYS
of
this LMI system. This MATLAB description of the problem can be
forwarded to other LMI-Lab functions for subsequent processing. The
command getlmis
must be used only once and
after declaring all matrix variables and LMI
terms.
Here the identifiers X
and S
point
to the variables X and S while
the tags BRL
, Xpos
, and Slmi
point
to the first, second, and third LMI, respectively. Note that –Xpos
refers
to the right-hand side of the second LMI. Similarly, –X
would
indicate transposition of the variable X.
getlmis
| lmiterm
| lmivar
| setlmis