Time-Varying Dynamics of a Micro Air Vehicle with Variable-Sweep Morphing

Chakravarthy, Animesh; Grant, Douglas D.; Lind, Rick

doi:10.2514/1.55078

Cited by 59 publications

(20 citation statements)

References 41 publications

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“…The remaining aerodynamic parameters are assumed to show somewhat smaller variations during the morphing trajectory and are taken to be constant. The representation of a morphing aircraft (that has independent shape and flight control), as a linear time varying (LTV) system has been discussed earlier [18][19][20] in the literature.…”

Section: Morphing Aircraftmentioning

confidence: 99%

See 1 more Smart Citation

Single Network Adaptive Critic (SNAC) Architecture for Optimal Tracking Control of a Morphing Aircraft during a Pull-up Maneuver

Nobleheart

Lakshmikanth

Chakravarthy

et al. 2013

AIAA Guidance, Navigation, and Control (GNC) Conference

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In this paper, we discuss the application of a Single Network Adaptive Critic (SNAC) tracking controller on a morphing fighter aircraft modeled as a time-varying system. The performance of the aircraft is investigated from a flight dynamics perspective during a pull-up maneuver; and the time scale over which the morphing occurs is of the same order as the flight dynamics, due to which the influence of time-varying effects is significant. The time varying dynamical equations are adopted for a fighter aircraft which is assumed to be equipped with a variable-sweep wing. The SNAC controller is implemented on the longitudinal dynamic model of this aircraft. The neural network is trained to provide optimal tracking control over the aircraft flight envelope state space as the wing is swept along a specific morphing trajectory during the maneuver. Nomenclaturek = discrete time index j = sweep angle trajectory index = state input = co-state = control = lift-curve slope = static longitudinal stability derivative coefficient = sweep angle = time = System matrix = Control matrix = longitudinal velocity = normal velocity = pitch rate = pitch angle S = solution of Joseph stabilized version of Riccati equation Q = State weighting matrix R = Control weighting matrix = sampling time tol = training tolerance

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Section: Morphing Aircraftmentioning

confidence: 99%

“…The introduction of morphing, or shape-changing actuation, to an aircraft will alter the shape and aerodynamics of the vehicle and so is a clear cause of time-varying effects [18][19][20] . These time-varying effects can have a profound influence on system performance and must be considered for some applications.…”

Section: Introductionmentioning

confidence: 99%

Single Network Adaptive Critic (SNAC) Architecture for Optimal Tracking Control of a Morphing Aircraft during a Pull-up Maneuver

Nobleheart

Lakshmikanth

Chakravarthy

et al. 2013

AIAA Guidance, Navigation, and Control (GNC) Conference

Self Cite

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“…When the rate of morphing is of the same order of magnitude as the flight dynamics of the aircraft, morphing becomes a clear cause of time-varying effects. [10][11][12] The focus of this paper is an elastically shaped aircraft 13-15 that has highly flexible wings, whose shape can be actively controlled in flight. More precisely, the wing twist and bending can be altered in flight so as to achieve a local angle of attack distribution that is optimal for the specific flight condition, the optimality being in the context that the wing shape results in lower drag and as a consequence, lower fuel consumption.…”

Section: Introductionmentioning

confidence: 99%

Optimal and Decentralized Controller Designs for an Elastically Shaped Aircraft

Nobleheart

Chakravarthy

Nguyen

2014

55th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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In this paper, control design of an elastically shaped aircraft with highly flexible wings is discussed. The aircraft has the capability to actively change the wing twist and bending in flight so as to achieve a local angle of attack distribution that is optimal for the specific flight condition. The aircraft has 23 control surfaces and is longitudinally unstable in the open loop. Two design approaches are explored. In the first approach, a multi-objective performance index that includes an explicit drag minimization term is considered, and an optimal controller design is performed using this performance index. In the second approach, a decentralized controller that uses the elevator to control only the rigid body modes, and the wing flap and slat control surfaces to control the flexible modes, is developed. Simulation results demonstrate the validity of these controllers in stabilizing this elastic aircraft.

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“…In addition, the dynamic equations are converted into switched system in several special points in [8], and then a finite-time boundedness controller is proposed to guarantee steady flight in the morphing process. Furthermore, in [9], the time varying characteristic equation based on the linear time-invariant characteristic equation and the concept of time varying pole are posed to analysis the time-varying dynamic mode of variable-sweep morphing. In [10], an active disturbance rejection controller is proposed based on ADRC without LPV or switched model while the un-modeled dynamics and aerodynamics are observed and compensated as a generalized disturbance in real time.…”

mentioning

confidence: 99%

Nonlinear robust adaptive NN control for variable-sweep aircraft

Ma¹,

Feng²,

Hu³

et al. 2018

J. vibroeng.

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In this paper, we address the problem of altitude and velocity controllers design for variable-sweep aircraft with model uncertainties. The object is to maintain altitude and velocity during the wing transition process where mass distribution and aerodynamic parameters change significantly. Based on the functional decomposition, the longitudinal dynamics of the aircraft can be divided into altitude subsystem in non-affine pure feedback form and velocity subsystem. And then nonlinear robust adaptive NN velocity controller and altitude controller are designed with backstepping method to relax the prior requirements of aerodynamic parameters accuracy in linear LPV controller design. The method of filtered signal is used to circumvent the algebraic loop problem caused by the dynamics of non-affine pure feedback form. Dynamic surface control (DSC) and minimal learning parameters (MLP) techniques are employed to solve the problems of 'explosion of complexity' in the back-stepping method and the online updated parameters being too much. The robust terms have been introduced to eliminate the influences of approximation errors. According to the Lyapunov-LaSalle invariant set theorem, the semi-global boundedness and convergence of all the signals of the closed-loop system are proved. Simulation results are presented to illustrate the control algorithm with good performance.

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Time-Varying Dynamics of a Micro Air Vehicle with Variable-Sweep Morphing

Cited by 59 publications

References 41 publications

Single Network Adaptive Critic (SNAC) Architecture for Optimal Tracking Control of a Morphing Aircraft during a Pull-up Maneuver

Single Network Adaptive Critic (SNAC) Architecture for Optimal Tracking Control of a Morphing Aircraft during a Pull-up Maneuver

Optimal and Decentralized Controller Designs for an Elastically Shaped Aircraft

Nonlinear robust adaptive NN control for variable-sweep aircraft

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