Specify matrix variables in LMI problem
X = lmivar(type,struct) [X,n,sX] = lmivar(type,struct)
lmivar defines a new matrix
variable X in the LMI system currently described.
The optional output
X is an identifier that can
be used for subsequent reference to this new variable.
The first argument
type selects among available
types of variables and the second argument
further information on the structure of X depending
on its type. Available variable types include:
type=1: Symmetric matrices with a block-diagonal structure. Each diagonal block is either full (arbitrary symmetric matrix), scalar (a multiple of the identity matrix), or identically zero.
If X has R diagonal blocks,
an R-by-2 matrix where
struct(r,1) is the size of the r-th
struct(r,2) is the type of the r-th
block (1 for full, 0 for scalar, –1 for zero block).
type=2: Full m-by-n rectangular
struct = [m,n] in this case.
type=3: Other structures. With Type 3, each entry of X is specified as zero or ±x where xn is the n-th decision variable.
struct is a matrix of the same
dimensions as X such that
struct(i,j)=0 if X(i,
j) is a hard zero
struct(i,j)=n if X(i,
j) = xn
struct(i,j)=–n if X(i,
j) = –xn
Sophisticated matrix variable structures can be defined with
Type 3. To specify a variable X of Type 3, first
identify how many free independent entries are
involved in X. These constitute the set of decision
variables associated with X. If the problem already
involves n decision variables, label the new free
variables as xn+1,
. . ., xn+p. The structure
of X is then defined in terms of xn+1,
. . ., xn+p as indicated
above. To help specify matrix variables of Type 3,
returns two extra outputs: (1) the total number n of scalar decision
variables used so far and (2) a matrix
the entry-wise dependence of X on the decision
variables x1, . . ., xn.
Consider an LMI system with three matrix variables , , and such that
is a 3-by-3 symmetric matrix (unstructured),
is a 2-by-4 rectangular matrix (unstructured),
where Δ is an arbitrary 5-by-5 symmetric matrix, and are scalars, and denotes the identity matrix of size 2.
Define these three variables using
setlmis() X1 = lmivar(1,[3 1]); % Type 1 X2 = lmivar(2,[2 4]); % Type 2 of dimension 2-by-4 X3 = lmivar(1,[5 1;1 0;2 0]); % Type 1
The last command defines as a variable of Type 1 with one full block of size 5 and two scalar blocks of sizes 1 and 2, respectively.
Combined with the extra outputs
lmivar, Type 3 allows you to specify fairly complex matrix variable structures. For instance, consider a matrix variable X with structure given by:
where and are 2-by-3 and 3-by-2 rectangular matrices, respectively. Specify this structure as follows.
Define the rectangular variables and .
setlmis() [X1,n,sX1] = lmivar(2,[2 3]); [X2,n,sX2] = lmivar(2,[3 2]);
sX2 give the decision variable content of
sX1 = 1 2 3 4 5 6
sX2 = 7 8 9 10 11 12
sX2(1,1) = 7 means that the (1,1) entry of
is the seventh decision variable.
Next, use Type 3 to specify the matrix variable X, and define its structure in terms of the structures of and .
[X,n,sX] = lmivar(3,[sX1,zeros(2);zeros(3),sX2]);
Confirm that the resulting
X has the desired structure.
sX = 1 2 3 0 0 4 5 6 0 0 0 0 0 7 8 0 0 0 9 10 0 0 0 11 12