ECE 501: 2nd Midterm: Solution - Fall 1998

  1. The equation:

    Riccati

    is the most general form of an algebraic Riccati equation (all matrices are assumed to be of sizes n×n.

    We define the matrix:

    Riccati

    as the generalized Hamiltonian matrix associated with this Riccati equation.

    Let:

    Riccati

    be the right model matrix of H, such that:

    Riccati

    is its spectral decomposition, i.e.:

    Riccati

    Show that, if V1 is non-singular, then:

    Riccati

    is a solution of the generalized matrix Riccati equation.

    We start by plugging the proposed solution into the generalized matrix Riccati equation:

    Riccati

    We decompose the eigenvector/eigenvalue matrix equation into its four component (still matrix) equations:

    Riccati

    Let us solve the first of these equations for L1:

    Riccati

    Plugging this into the third equation, we obtain:

    Riccati

    Multiplying this equation from the right with V1-1, one gets:

    Riccati

    which is the same as above except for the ordering of the terms.

     

  2. Given the system:

    Riccati

    We often like to have this system together with the state feedback:

    Riccati

    behave like the model:

    Riccati

    where:

    Riccati

    One way to reformulate this problem is:

    Riccati

    Thus:

    Riccati

    or:

    Riccati

    We want to reformulate this performance index in terms of a problem that we already know:

    Riccati

    Find:

    Riccati

    Then develop a Matlab code:

    Riccati

    implementing the model follower optimal control problem.

    By differentiating the output equation, we find:

    Riccati

    and therefore:

    Riccati

    Plugging this expression into the performance index, one obtains:

    Riccati

    The terms can be rearranged as follows:

    Riccati

    and assuming that:

    Riccati

    one can find:

    Riccati

    This can now easily be programmed into Matlab:

    
              function [K,P] = modfol(A,B,C,Am,Q,R)
                H1 = C*A - Am*C;
                H2 = C*B;
                Qh = H1'*Q*H1;
                Nh = H1'*Q*H2;
                Rh = R + H2'*Q*H2;
                [K,P] = lqr(A,B,Qh,Rh,Nh);
              return
          

     

  3. Given the system:

    Riccati

    Design a functional observer for this system, such that the closed-loop poles are at the locations:

    Riccati

    and the observer poles are at the locations:

    Riccati

    Find a 2-input / 1-output realization of this system:

    Riccati

    where:

    Riccati

    The open-loop denominator polynomial is:

    Riccati

    The numerator polynomial (both open- and closed-loop) is:

    Riccati

    The observer denominator polynomial is:

    Riccati

    and the desired closed-loop denominator polynomial is:

    Riccati

    Therefore:

    Riccati

    Hence, the functional observer equations can be computed from the matrix equation:

    Riccati

    The resulting c-vector is:

    Riccati

    Thus, the two feedback filter polynomials are:

    Riccati

    and:

    Riccati

    Thus, the feedback system can theoretically be realized as follows:

    Riccati

    However, the gains are far too large for this system to be realizable in a meaningful fashion. The open-loop system has the poles so far away from the desired closed-loop poles, that the desired goals cannot be reached by realistic means.

     

  4. Given the system:

    Riccati

    Find the Gilbert realization of this system.

    First, we need to separate the strictly proper subsystem from the direct input output gain:

    Riccati

    Now, we can perform a partial fraction expansion on the strictly proper subsystem:

    Riccati

    Thus, R1 is:

    Riccati

    and R2 is:

    Riccati

    This leads to the state-space description:

    Riccati