Abstract :
We revisit the approach by Cao et al. that uses a fixed-structure control law to find stabilizing static output feedback gains for linear time-invariant systems. By performing singular value decomposition on the output matrix, together with similarity transformations, we present a new stabilization method. Unlike their results that involve a difficult modified Riccati equation whose solution is coupled with other two intermediate matrices that are difficult to find, we obtain Lyapunov equations. We present a convergent algorithm to solve the new design equations for the gains. We will show that our new approach, like theirs, is a dual optimal output feedback linear quadratic regulator theory. Numerical examples are given to illustrate the effectiveness of the algorithm and validate the new method.
Keywords :
Lyapunov methods; continuous time systems; feedback; linear quadratic control; matrix algebra; singular value decomposition; stability; Lyapunov equations; convergent algorithm; dual optimal output feedback linear quadratic regulator theory; output matrix; similarity transformations; singular value decomposition; stabilizing static output feedback gains; Algorithm design and analysis; Control systems; Gain; Linear feedback control systems; Linear matrix inequalities; Matrix decomposition; Output feedback; Regulators; Riccati equations; Singular value decomposition;