Reduced-Order Optimal Feedback Control Law Synthesis for Flutter Suppression

Abstract

A method of synthesizing reduced-order optimal feedback control laws for a high-order system is developed. A nonlinear programming algorithm is employed to search for the control law design variables that minimize a performance index defined by a weighted sum of mean-square steady-state responses and control inputs. An analogy with the linear quadratic Gaussian solution is utilized to select a set of design variables and their initial values. An input-noise adjustment procedure is used in the design algorithm to improve the stability margins of the system. The method is applied to the synthesis of an active flutter-suppression control law for an aeroelastic wind tunnel wing model. The reduced-order control law is compared with the corresponding full-order control law. The study indicates that by using the present algorithm, near optimal low-order flutter suppression control laws with good stability margins can be synthesized.