Adaptive control of hypersonic vehicles in presence of aerodynamic and center of gravity uncertainties

Somanath, Amith; Annaswamy, Anuradha M.

doi:10.1109/cdc.2010.5717494

Cited by 20 publications

(9 citation statements)

References 16 publications

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“…The important results from those studies are outlined here. Somanath and Annaswamy [3] present an adaptive controller for systems with partially known input matrix B. The controller that is presented is globally asymptotically stable when only information regarding the structure of B is known.…”

Section: Introductionmentioning

confidence: 98%

L1 Adaptive Control Augmentation Configuration for a Hypersonic Glider in the Presence of Uncertainties

Banerjee

Creagh

Boyce

et al. 2014

AIAA Guidance, Navigation, and Control Conference

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The descent longitudinal trajectory control methodology of a hypersonic glider is presented. The overall desired trajectory is presented, followed by a basic analysis of the control methodology used to carry out a pull up maneuver; bringing the glider from a descent trajectory to horizontal flight. A dynamic pole placement controller is implemented to carry out this maneuver. This controller is augmented with an adaptive controller to cancel out the matched uncertainties. Only the longitudinal dynamics are considered in this analysis. The fundamental differences between only the pole placement and the augmented pole placement with the adaptive controller are presented in terms of robust stability and robust performance. When the INS/GPS module is turned on, of the altitude error, flight path angle error and angle of attack error are bounded compared to the unfiltered values. The dynamic pole placement controller is shown to have robustness in the presence of time invariant, Gaussian and time varying errors in the aerodynamic coefficients. The augmentation set up improves the performance of the baseline controller in the presence of these uncertainties. With the help of Monte Carlo Simulations the performance, robustness and stability bounds of the baseline and the adaptive augmented controller are presented and are compared to the performance of the pole placement controller. All the simulations and implementations are carried out in CADAC++ which is written in C++. The system presented is a nonminimum phase system. The uncertainties presented in this paper are matched uncertainties. The main contribution of this paper lies in the application and determining robustness and performance of a piecewise constant augmentation setup to a Linear Time Varying (LTV) System. Nomenclature , = body, inertial coordinates , , = roll, pitch and yaw principle moments of inertia, kgm 2 = component xy of moment of inertia matrix, kgm 2 = closed loop system matrix = desired closed loop system matrix = plant model system matrix = body acceleration with respect to inertial frame = input gain matrix = output matrix = wing chord length, m = reference length, m = drag force, N ( ) = tracking error dynamics = state transition matrix = control coefficient matrix = pitch moment of inertia, kgm 2 , = angle of attack autopilot feedback gains ! = lift force, N ! " = lift coefficient slope as a function of angle of attack, m/s 2 ! #$ = dimensional lift slop with elevator deflection derivative, m/s 2 = pitching moment control derivative, 1/s 2 ) "= dimensional normal force slope derivative, m/s 2 ) #$ = normal force slope with elevator deflection derivative, m/s 2 * = pitch rate, rad/s + = pitch rate, rad/s + = rate of change of pitch rate , = velocity vector -= state vector -.= state estimate vector / 0 = output estimate 1 = angle of attack, rad 1 = rate of change of angle of attack, rad/s 2 = elevator deflection command 3 4 5 6 = multiplicative uncertainty in longitudinal stability 3 4 7 6 = multiplicative uncertainty in lift coefficient 3 4 ...

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Section: Introductionmentioning

confidence: 98%

L1 Adaptive Control Augmentation Configuration for a Hypersonic Glider in the Presence of Uncertainties

Banerjee

Creagh

Boyce

et al. 2014

AIAA Guidance, Navigation, and Control Conference

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“…Chemori and Marchand used a partial feedback linearization combined with optimal trajectory generation to stabilize the internal dynamics. An adaptive controller is presented in the work of Somanath and Annaswamy for the linearized model of the HSV considered in our work. The proposed method focuses on the adaptation to the partially known control coefficient matrix.…”

Section: Introductionmentioning

confidence: 99%

A modular adaptive control design with ISS analysis for nonminimum phase hypersonic vehicle models

Mannava

Serrani

2018

Adaptive Control & Signal

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Air-breathing hypersonic vehicles typically exhibit a nonminimum phase behavior when altitude is controlled via lift generation. This phenomenon prohibits the use of classical inversion-based control techniques. Dynamic models of these vehicles are also subject to parametric uncertainties and unmodeled dynamics related to flexible effects of the fuselage. In this paper, we present a modular adaptive control method that achieves asymptotic setpoint tracking in both airspeed and altitude using thrust and elevator deflection as the only control inputs for a generic longitudinal model of a hypersonic cruise. The nonminimum phase problem is overcome through output redefinition, with altitude controlled by pitching moment. The internal dynamics, flight path angle, and altitude are then stabilized by saturating the interconnections and exploiting local stability properties. A new technique for the use of saturation functions in error coordinate is presented. The adaptive controller for altitude uses a pitch rate observer combined with projection. This control augmentation decouples the parameter estimation errors from internal dynamics, allowing for the use of small-gain arguments. Simulation results from a vehicle model with flexible effects and parametric uncertainty are included to demonstrate control effectiveness. KEYWORDS adaptive control, hypersonic vehicles, input-to-state stability, nonminimum phase systems 816

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“…A significant amount of literatures has been devoted to the attitude control of hypersonic vehicles from various perspectives. When treating the nonlinear model directly, the adaptive control [4,5], the robust control [6,7], and the sliding mode control [8] are some of the most popular methods. The dynamic inversion control, which provides an effective way to overcome the nonlinearity of the system, has also been investigated in quite a few literatures [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Characteristic model-based H 2/H ∞ robust adaptive control during the re-entry of hypersonic cruise vehicles

Huang

Zhang

2014

Sci. China Inf. Sci.

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This paper aims at introducing H 2 and H∞ robustness into the well-known characteristic modelbased golden-section adaptive control law, and applying the robust adaptive control scheme to the attitude control of hypersonic cruise vehicles that are subject to external disturbances and aerodynamic coefficients uncertainties. When maneuvering at ultra high speeds, the attitude system of the hypersonic cruise vehicle is extremely sensitive to external disturbances and aerodynamic coefficients variations, and therefore the adaptiveness and the robustness of the attitude system are crucial during the controller design. To enhance the robustness of the existing golden-section adaptive control law, a golden-section robust adaptive control law is proposed. Compared to the existing control law where the design of the parameter λ depends on experience and is carried out offline, linear matrix inequality-based synthesis of λ is proposed such that the closed-loop system is stable with guaranteed H 2 and H∞ performance. It is suitable for online computing and provides a time-varying λ(k) that is adjusted towards the optimal H 2 and H∞ performance. When being applied to the attitude control of hypersonic vehicles during re-entry, the adaptive nature of the proposed control law provides the attitude system the capability to accommodate large flight conditions, and its H 2 and H∞ robustness brought by λ(k) guarantees satisfying tracking performance in the presence of disturbances including both external disturbance and absolute aerodynamic coefficients errors. Keywords golden-section adaptive control, characteristic model, H 2 and H∞ analysis, hypersonic vehicle, attitude control Citation Huang H, Zhang Z. Characteristic model-based H2/H∞ robust adaptive control during the re-entry of hypersonic cruise vehicles.

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Adaptive control of hypersonic vehicles in presence of aerodynamic and center of gravity uncertainties

Cited by 20 publications

References 16 publications

L1 Adaptive Control Augmentation Configuration for a Hypersonic Glider in the Presence of Uncertainties

L1 Adaptive Control Augmentation Configuration for a Hypersonic Glider in the Presence of Uncertainties

A modular adaptive control design with ISS analysis for nonminimum phase hypersonic vehicle models

Characteristic model-based H 2/H ∞ robust adaptive control during the re-entry of hypersonic cruise vehicles

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