This paper describes some activities associated with the preliminary design of an active control system for flutter suppression capable of demonstrating a 20% increase in flutter velocity. Results from two control system synthesis techniques are given. One technique uses classical control theory, and the other uses an "aerodynamic energy method," where control surface rates or displacements are minimized. Analytical methods used to synthesize the control systems and evaluate their performance are described. Some aspects of a program for flight testing the active control system are also given. This program, Drones for Aerodynamics and Structural Testing (DAST), employs modified drone-type vehicles for flight assessments and validation testing.1> a 2 b D(s) g h h r k k m M N(s) s V y y* a. Oir 6 P CO f Matrices Nomenclature = generalized aerodynamic force = control law gains used in energy method -reference semichord used in aerodynamic theory = chord length along centerline of control surface = semichord length along centerline of control surface, c/2 -denominator polynomial in 5 -units of gravitational acceleration -vertical displacement at 30% of wing chord c -vertical displacement at fuselage reference point = reduced frequency, coZ?/ V -aerodynamic lag = Mach number = numerator polynomial in s -Laplace variable = flight velocity = sensor output = fraction of wing semispan, measured from fuselage centerline = angle of attack of wing at wing chord c = angle of attack of fuselage at fuselage reference point = control surface displacement = atmospheric density = circular frequency = damping coefficient = real aerodynamic matrix coefficients = real aerodynamic matrix coefficients control surfaces = control surface input matrix = real coefficients of equations of motion = seeEq. (6) for [/] = identity matrix [K] = generalized stiffness [M] = generalized mass (M 6 } = mass unbalance of control surface |_T(5)J = transfer function relating control surface response to wing motion [q] = generalized displacement vector [ U] = matrix representing first-order equations of motion [X] = response vector of first-order equations of r 7 ^ motion | M = displacement at sensor locations [>] = matrix of modal coefficients at sensor locations . . . = dot superscripts, indicate time derivativesIntroduction jVER the last several years considerable interst has 'emerged in applying active control technology to suppress aeroelastic response of present and future aircraft. l~3 Application of this technology offers potential gains in aerodynamic efficiency and weight savings by providing ride quality control, gust and maneuver load control, flutter suppression, and by allowing for relaxed static stability. Through cooperative interdisciplinary efforts, especially among control specialists and aeroelasticians, a new class of aircraft may evolve in which active control systems are integrated into the initial vehicle design, and structural integrity is dependent on the adequate operation of an active control system.A considerable amount of e...