Control Law Synthesis for Flutter Suppression Using Linear Quadratic Gaussian Theory

Mahesh, J. K.; Stone, C. R.; Garrard, William L.; Dunns, H.J.

doi:10.2514/3.56094

Cited by 56 publications

(11 citation statements)

References 8 publications

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“…3) The standard deviation of the wind-speed measurement should be small, at least in the range of [2][3][4] m=s.…”

Section: Analysis Of the Feedforward Controllermentioning

confidence: 99%

“…Nonadaptive feedback control algorithms, such as the classical single input/single output (SISO) techniques [1], the linear quadratic regulator theory [2,3], the eigenspace techniques [4,5], the optimal control algorithm [6], and the H 1 robust control synthesis technique [7] are efficient methods for the gust load alleviation/flutter suppression. However, because of the time-varying characteristics of the aircraft dynamics due to the varying configurations and operational parameters (such as fuel consumption, air density, velocity and air turbulence), it is difficult to synthesize a unique control law to work effectively throughout the whole flight envelope.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Feedforward Control for Gust Load Alleviation

Zeng

Moulin

Callafon

et al. 2010

Journal of Guidance, Control, and Dynamics

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In this paper, an adaptive feedforward control framework is proposed for the suppression of aircraft structural vibrations induced by gust perturbations to increase the resilience of the flight control law in the presence of the aeroelastic/aeroservoelastic interactions. Currently, aircraft with nonadaptive control laws usually include roll-off or notch filters to avoid aeroelastic/aeroservoelastic interactions. However, if changes in the aircraft configuration are significant, the frequencies of the flexible modes of the aircraft may be shifted, and the notch filters could become totally ineffective. With the proposed approach, the flexible modes can be consistently estimated in real time via a proven system-identification algorithm. The identified flexible modes information is used in the proposed adaptive feedforward control algorithm to adjust the parametrization of the basis functions in a feedforward controller. Along with the recursive least-squares estimate, the feedforward controller is adjusted, and the structural vibration of the aircraft induced by the gust perturbation can be largely suppressed. An F/A-18 active aeroelastic wing aeroelastic model with gust perturbation based on the linear aeroelastic solver formulation is developed as a test bed to demonstrate the proposed adaptive feedforward control algorithm. Nomenclature A! = denominator matrix polynomial B! = numerator matrix polynomial B i q = orthonormal basis function C = damping matrix Fq = feedforward compensator F A = external aerodynamic forces F T = thrust forces F = aerodynamic forces from control surfaces Gq = transfer function from control surface to accelerometer sensor G! = frequency response function Hq = transfer function from gust perturbation to accelerometer sensor K = stiffness matrix kt = gain vector M = mass matrix M A = external aerodynamic moments M T = thrust moments M = aerodynamic moments from control surfaces Pq = all pass transfer function Pt = inverse correlation matrix Qs = aerodynamic force coefficient matrix q = forward shift operator T A = transformation matrix T g s = Dryden vertical velocity shaping filter T LPF s = low-pass filter ut = control surface command wt = gust perturbation x Le = aerodynamic lag terms yt = output signal k = coefficients of the orthonormal finite impulse response filter F = aeroelastic incremental forces M = aeroelastic incremental moments e = generalized coordinate = unknown parameters to be estimated = forgetting factor t = regress vector Subscripts ee = related to the elastic dynamics i = r; e; related to the airframe, elastic, control related states lat = related to the lateral dynamics plane long = related to the longitudinal dynamics plane re = related to the coupling between rigid-body dynamics and elastic dynamics rr = related to the rigid-body dynamics

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“…3) The standard deviation of the wind-speed measurement should be small, at least in the range of [2][3][4] m=s.…”

Section: Analysis Of the Feedforward Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive Feedforward Control for Gust Load Alleviation

Zeng

Moulin

Callafon

et al. 2010

Journal of Guidance, Control, and Dynamics

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“…We will demonstrate that, in the example flutter suppression system, proper placement of accelerometers will result in minimum phase systems with good robustness and conversely, that improper placement of the accelerometers results in right half-plane zeros and subsequent degradation in system rms performance and stability robustness. For the two control cases, the combined regulator-observer system robustness will be measured in terms of the minimum singular value of the following return difference matrix: (8) In all numerical examples that follow, the filter gains L are determined from Kalman filter theory with measurement noise intensity equal to the identity matrix and plant noise intensity equal to BB T . …”

Section: -Bkmentioning

confidence: 99%

Accelerometer placement in active flutter suppression systems

Liebst

1987

Journal of Guidance, Control, and Dynamics

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An elementary study of the placement of accelerometers when used as sensors in active flutter suppression systems is presented, The model analyzed is a two-dimensional typical section with various combinations of leading-and trailing-edge controllers. The relationship between the control surf ace placement and accelerometer placement is examined. The results for the numerical examples presented show that accelerometers must be on the same side of the center of gravity as the control surface or right half-plane transmission zeros will arise. The detrimental effects of the right half-plane zeros are discussed in the context of linear-quadratic-regulator plus loop-transfer-recovered observer designs.Nomenclature distance elastic axis is aft of the midchord, nondimensionalized by b state matrix, see Eq. (5) sernichord of section, c/2 control influence matrix, see Eq. (5) chord of section measurement matrix, see Eq. (6) distance leading-edge controller ningeline is aft of the midchord, nondimensionalized by b distance trailing-edge controller hingeline is aft of the midchord, nondimehsionalized by b downward displacement of elastic axis downward displacement of accelerometer position identity matrix moment of inertia per unit length of section about the elastic axis • -regulator gain matrix = stiffness of section in deflection = torsional stiffness of section about elastic axis = distance accelerometer is aft of elastic axis, nondimensionalized by b • -observer gain matrix ' • • lift per unit span = slope dL/da. -2irpU 2 b • • slope dL/dp L = 2(T 10 -7r)pU 2 b • -slope dL/dp T = 2T w^p U 2 b • -mass per unit length of section = aerodynamic moment per unit span about elastic axis = slope dM/da = 2irpb 2 U 2 (a + 1/2) = slope dM/d$ L = pb 2 U 2 [2aT w -T 4 -2

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“…Amount others, non-adaptive feedback control algorithms such as linear quadratic regulator (LQR) theory [10,11], eigenspace techniques [12,13], optimal control algorithms [14], H∞ robust control synthesis technique [15]. All of them offer a high performance fixed-parameters control law when plant parameters are known under a linear formulation of the aircraft model.…”

Section: Introductionmentioning

confidence: 99%

A new pitch angle adaptive control design

Viúdez‐Moreiras

Martin

Martín‐Sánchez

2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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This paper presents a new pitch angle adaptive control design based on the pitch rate following of a desired trajectory that ensures closed loop satisfactory performance. The pitch rate is under adaptive predictive (AP) control, as previously seen in the literature, but its desired trajectory is produced by a guidance block within a global guidance system structure that ensures automatic pitch angle closed loop performance. Additionally, the guidance block presented in this paper allows satisfactory operation of the automatic pilot in a range of high control frequencies suitable for this kind of application, overcoming stability problems that may arise within these high frequencies by direct application of a pitch angle AP controller. Experimental results obtained by flying a simulated aircraft illustrate comparatively the guidance system performance, and show the robustness of the new design with aerodynamic disturbances.

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Control Law Synthesis for Flutter Suppression Using Linear Quadratic Gaussian Theory

Cited by 56 publications

References 8 publications

Adaptive Feedforward Control for Gust Load Alleviation

Adaptive Feedforward Control for Gust Load Alleviation

Accelerometer placement in active flutter suppression systems

A new pitch angle adaptive control design

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