Controllability Gramian

Summary

In control theory, we may need to find out whether or not a system such as

is controllable, where , , and are, respectively, , , and matrices for a system with inputs, state variables and outputs.

One of the many ways one can achieve such goal is by the use of the Controllability Gramian.

Controllability in LTI Systems edit

Linear Time Invariant (LTI) Systems are those systems in which the parameters  ,  ,   and   are invariant with respect to time.

One can observe if the LTI system is or is not controllable simply by looking at the pair  . Then, we can say that the following statements are equivalent:

  1. The pair   is controllable.
  2. The   matrix
     
    is nonsingular for any  .
  3. The   controllability matrix
     
    has rank n.
  4. The   matrix
     
    has full row rank at every eigenvalue   of  .

If, in addition, all eigenvalues of   have negative real parts (  is stable), and the unique solution of the Lyapunov equation

 
is positive definite, the system is controllable. The solution is called the Controllability Gramian and can be expressed as
 

In the following section we are going to take a closer look at the Controllability Gramian.

Controllability Gramian edit

The controllability Gramian can be found as the solution of the Lyapunov equation given by

 

In fact, we can see that if we take

 
as a solution, we are going to find that:
 

Where we used the fact that   at   for stable   (all its eigenvalues have negative real part). This shows us that   is indeed the solution for the Lyapunov equation under analysis.

Properties edit

We can see that   is a symmetric matrix, therefore, so is  .

We can use again the fact that, if   is stable (all its eigenvalues have negative real part) to show that   is unique. In order to prove so, suppose we have two different solutions for

 
and they are given by   and  . Then we have:
 

Multiplying by   by the left and by   by the right, would lead us to

 

Integrating from   to  :

 
using the fact that   as  :
 

In other words,   has to be unique.

Also, we can see that

 
is positive for any t (assuming the non-degenerate case where   is not identically zero). This makes   a positive definite matrix.

More properties of controllable systems can be found in Chen (1999, p. 145), as well as the proof for the other equivalent statements of “The pair   is controllable” presented in section Controllability in LTI Systems.

Discrete Time Systems edit

For discrete time systems as

 

One can check that there are equivalences for the statement “The pair   is controllable” (the equivalences are much alike for the continuous time case).

We are interested in the equivalence that claims that, if “The pair   is controllable” and all the eigenvalues of   have magnitude less than   (  is stable), then the unique solution of

 
is positive definite and given by
 

That is called the discrete Controllability Gramian. We can easily see the correspondence between discrete time and the continuous time case, that is, if we can check that   is positive definite, and all eigenvalues of   have magnitude less than  , the system   is controllable. More properties and proofs can be found in Chen (1999, p. 169).

Linear Time Variant Systems edit

Linear time variant (LTV) systems are those in the form:

 

That is, the matrices  ,   and   have entries that varies with time. Again, as well as in the continuous time case and in the discrete time case, one may be interested in discovering if the system given by the pair   is controllable or not. This can be done in a very similar way of the preceding cases.

The system   is controllable at time   if and only if there exists a finite   such that the   matrix, also called the Controllability Gramian, given by

 
where   is the state transition matrix of  , is nonsingular.

Again, we have a similar method to determine if a system is or is not a controllable system.

Properties of Wc(t0,t1) edit

We have that the Controllability Gramian   have the following property:

 
that can easily be seen by the definition of   and by the property of the state transition matrix that claims that:
 

More about the Controllability Gramian can be found in Chen (1999, p. 176).

See also edit

References edit

  • Chen, Chi-Tsong (1999). Linear System Theory and Design Third Edition. New York, New York: Oxford University Press. ISBN 0-19-511777-8.

External links edit

  • Mathematica function to compute the controllability Gramian