General Lyapunov-Based Iterative Algorithm for Linear Quadratic
Regulator Problem of Stochastic Systems with Markovian Jump
Abstract
This paper investigates the linear quadratic regulator(LQR) problem of
linear stochastic systems with Markovian jump. Firstly, two iterative
algorithms are proposed for solving the corresponding coupled algebraic
Riccati equa- tions (CAREs) based on the general-type Lyapunov equation
derived from linear stochastic systems. It is verified that the second
algorithm adding an adjustable factor converges faster than the first
one without it. Secondly, a monotonic convergence theorem is established
for the proposed iterative algorithms under certain initial conditions.
In the end, a numerical example is given to verify the efficiency of the
proposed algorithms.