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Linear quadratic Gaussian (LQG) optimization is often used in aviation and space applications. Over three dozens of examples for such applications from the COMPleib benchmark collection are used in this paper to investigate the performance of a new Newtontype algorithm to solve LQG problems. The algorithm efficiency and its accuracy, measured in terms of normalized and relative residuals of computed solutions of algebraic Riccati equations (AREs), are analyzed. Various stabilizing initializations, including that provided by the state-of-the-art MATLAB solver, are considered. The numerical results strongly recommend this algorithm especially for improving approximate solutions computed using other approaches.

ACCURATE LINEAR QUADRATIC OPTIMIZATION IN AVIATION AND SPACE APPLICATIONS