Multi-Input Noncertainty-Equivalent Adaptive Control of an Aeroelastic System

Lee, Keum W.; Singh, Sahjendra N.

doi:10.2514/1.48302

Cited by 51 publications

(33 citation statements)

References 30 publications

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“…Multi-input/multi-output control designs are used in papers [8,12,23]. However, the actuator dynamics are not included in the models in those cases.…”

Section: Dmentioning

confidence: 99%

Tensor-Product-Model-Based Control of a Three Degrees-of-Freedom Aeroelastic Model

Takarics

Bárányi

2013

Journal of Guidance, Control, and Dynamics

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“…Multi-input/multi-output control designs are used in papers [8,12,23]. However, the actuator dynamics are not included in the models in those cases.…”

Section: Dmentioning

confidence: 99%

Tensor-Product-Model-Based Control of a Three Degrees-of-Freedom Aeroelastic Model

Takarics

Bárányi

2013

Journal of Guidance, Control, and Dynamics

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“…For the transformation the parameter space Ω is chosen as U ∈ [8,16] (m/s), α ∈ [−0.3, 0.3] (rad) andβ ∈ [−1.5, 1.5] (rad/s) and the grid as G 1 = G 2 = 141 and G 3 = 7500. The TP model transformation is carried out on the state-space qLPV model of the 3-DoF aeroelastic wing section model (Eq.…”

Section: ) Generating the Two Tp Model Representationsmentioning

confidence: 99%

Influence of the Manipulation of the Polytopic Tensor Product Model Representation on the Control Performance of LMI Based Design

Szollosi

Bárányi

Várlaki

2015

2015 IEEE International Conference on Systems, Man, and Cybernetics

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The paper studies the effect of the manipulation of the polytopic TP model representation of a given quasi Linear Parameter Varying (qLPV) state-space model on the control performance results. The investigated model in the case study consists of the extended, Stribeck friction included three degreesof-freedom version of the aeroelastic wing section of the Nonlinear Aeroelastic Test Apparatus (NATA) model. The investigation is carried out through the Tensor Product (TP) model transformation based Control Design Framework, which bridges the manipulation of the polytopic representation and Linear Matrix Inequality (LMI) based control design methods. Different TP model representations of the given qLPV model are derived: a TP model representation with a sum-normalized non-negative (SNNN) convex hull, a TP model representation with a closeto-normal (CNO) convex hull and interpolated TP model representations. Upon these representations Linear Matrix Inequality based design methods are applied to attain the controller and observer system components. The resulting control systems are tested through numerical simulation and their performance are compared and evaluated. The paper presents results, where the interpolated representations lead to better control performance results, which indicates, that the manipulation of the polytopic TP model representation may lead to further potential optimization possibilities. Also, this shows, that in order to find the optimal solution the manipulation is a necessary and important step.

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“…Researchers have developed several adaptive control systems for the control of this aeroelastic system with uncertainties, using single as well as two control surfaces [11,[13][14][15][16][17]. The design of a noncertainty-equivalent adaptive control system has been presented in [18]. Neural control laws for suppressing the LCOs have been designed in [15,19].…”

Section: Introductionmentioning

confidence: 99%

Multi-Input Higher-order Sliding Mode Control of Aeroelastic Systems With Uncertainties and Gust Load

Lee

Singh

2014

AIAA Guidance, Navigation, and Control Conference

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This paper presents the design of a higher-order sliding mode controller for finite-time stabilization of a multi-input multi-output nonlinear aeroelastic system with uncertain dynamics using leading-and trailing-edge control surfaces. The model describes the plunge and pitch dynamics of a prototypical wing section. It is assumed that the system parameters are not known precisely and external disturbance inputs are present in the model. The uncontrolled model exhibits limit cycle oscillations. The objective is to control the state vector of the system to the origin. A robust control law is designed for the finite-time trajectory control of the plunge and pitch angle trajectory. The control law includes a nominal finite-time stabilizing control signal designed for the system without uncertainties, and a discontinuous control signal for nullifying the effect of uncertain functions in the model. For the nominal control law design, the notion of geometric homogeneity is utilized and the discontinuous part of the controller is derived based on a second-order sliding mode control scheme. In the closed-loop system including the nominal and discontinuous control signals, finite-time control of the complete state vector associated with the plunge-pitch motion of the system to the origin is accomplished. Simulation results are presented which show the suppression of the limit cycle oscillations, despite parameter uncertainties and triangular, exponential, sinusoidal and random gust loads.

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Multi-Input Noncertainty-Equivalent Adaptive Control of an Aeroelastic System

Cited by 51 publications

References 30 publications

Tensor-Product-Model-Based Control of a Three Degrees-of-Freedom Aeroelastic Model

Tensor-Product-Model-Based Control of a Three Degrees-of-Freedom Aeroelastic Model

Influence of the Manipulation of the Polytopic Tensor Product Model Representation on the Control Performance of LMI Based Design

Multi-Input Higher-order Sliding Mode Control of Aeroelastic Systems With Uncertainties and Gust Load

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