Title :
An Asymptotically Exact Approach to Robust Semidefinite Programming Problems with Function Variables
Author_Institution :
Dept. of Syst. Design & Eng., Nanzan Univ., Seto
fDate :
5/1/2009 12:00:00 AM
Abstract :
This technical note provides an approximate approach to a semidefinite programming problem with a parameter-dependent constraint and a function variable. This problem covers a variety of control problems including a robust stability/performance analysis with a parameter-dependent Lyapunov function. In the proposed approach, the original problem is approximated by a standard semidefinite programming problem through two steps: first, the function variable is approximated by a finite-dimensional variable; second, the parameter-dependent constraint is approximated by a finite number of parameter-independent constraints. Both steps produce approximation error. On the sum of these approximation errors, this technical note provides an upper bound. This bound enables quantitative analysis of the approach and gives an efficient way to reduction of the approximation error. Moreover, this technical note discusses how to verify that an optimal solution of the approximate problem is actually optimal also for the original problem.
Keywords :
Lyapunov methods; approximation theory; linear matrix inequalities; robust control; approximation error; linear matrix inequalities; parameter-dependent Lyapunov function; parameter-dependent constraint; parameter-independent constraints; performance analysis; robust semidefinite programming; robust stability analysis; Approximation error; Functional programming; Linear matrix inequalities; Lyapunov method; Performance analysis; Robust stability; Robustness; Symmetric matrices; Upper bound; Vectors; Approximation error; exactness verification; linear matrix inequalities (LMIs); matrix dilation; parameter-dependent Lyapunov functions; robust semidefinite programming (robust SDP);
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2009.2017141