Nhan T. Nguyen

Coupled Vortex-Lattice Flight Dynamic Model with Aeroelastic Finite-Element Model of Flexible Wing Transport Aircraft with Variable Camber Continuous Trailing Edge Flap for Drag Reduction

This paper presents a coupled vortex-lattice flight dynamic model with an aeroelastic finite-element model to predict dynamic characteristics of a flexible wing transport aircraft. The aircraft model is based on NASA Generic Transport Model (GTM) with representative mass and stiffness properties to achieve a wing tip deflection about twice that of a conventional transport aircraft (10% versus 5%). This flexible wing transport aircraft is referred to as an Elastically Shaped Aircraft Concept (ESAC) which is equipped with a Variable Camber Continuous Trailing Edge Flap (VCCTEF) system for active wing shaping control for drag reduction. A vortex-lattice aerodynamic model of the ESAC is developed and is coupled with an aeroelastic finite-element model via an automated geometry modeler. This coupled model is used to compute static and dynamic aeroelastic solutions. The deflection information from the finite-element model and the vortex-lattice model is used to compute unsteady contributions to the aerodynamic force and moment coefficients. A coupled aeroelastic-longitudinal flight dynamic model is developed by coupling the finite-element model with the rigid-body flight dynamic model of the GTM.

A set-theoretic model reference adaptive control architecture for disturbance rejection and uncertainty suppression with strict performance guarantees

ABSTRACT Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.

Derivative-Free Output Feedback Adaptive Control of an Aeroelastic Generic Transport Model

This paper illustrates an application of derivative-free, output feedback adaptive control on an aeroelastic model of longitudinal dynamics for a generic transport model. The controller uses a state observer as a reference model, and has a derivative-free delayed weight update law. Since it does not assume the existence of constant ideal weights, it is particulary well suited for adaptation to sudden changes in system dynamics, such as might be due to reconfiguration, deployment of a payload, docking, structural damage, or to difficult to model external disturbances. In addition, it i s applicable to output feedback

Model Reference Neuroadaptive Control Revisited: How to Keep the System Trajectories on a Given Compact Set

We revisit the design of model reference neuroadaptive control laws. This class of control laws have the capability to approximate any system uncertainty with an unknown structure and parameters on a compact set using neural networks. Yet, a challenge in their design is to keep the controlled system trajectories on this compact set for satisfying the universal function approximation property. Motivated by this challenge, a new model reference neuroadaptive control architecture is proposed to keep the controlled system trajectories within a-priori, user-defined compact set while addressing disturbance rejection and system uncertainty suppression. The presented architecture is illustrated by a numerical example.

A Design, Analysis and Verification Framework for Adaptive Flight Control

Safety-critical aerospace systems require stringent stabilization or tracking performance that have to be guaranteed in the face of large system uncertainties and abrupt changes on system dynamics. Considering Model Reference Adaptive Control (MRAC) schemes, while aggressive adaptation rates can, theoretically, produce a fast convergence of the tracking error to zero, this is often achieved at the expense of high frequency chattering and peaking in the control signal that could be unacceptable for practical applications. Due to the inherent nonlinear nature of MRAC schemes it is not easy to rigorously predict the response of the uncertain adaptive systems especially during transients. This is testified by the lack of clear and easy verification procedures for existing adaptive control schemes that relate design parameters to time domain specifications. To face this problem, we propose a design and validation framework where stability and performance requirements for the adaptive system are all formulated in terms of Linear Matrix Inequalities. This brings the advantage that the adaptive controller design and verification can be analyzed and optimized through the solution of a convex optimization whose objective is to guarantee the evolution of the error components within an a-priori specified invariant set. This approach was applied to verify the performance of a recently introduced MRAC scheme featuring a feedback contribution in the reference model that is proportional to the current tracking error. This architecture is deemed particularly appropriate to face uncertainty in real applications. A detailed design example applied to a generic flexible structure aircraft transport model is presented to highlight the efficacy of the proposed verification architecture.

Stability limit of human-in-the-loop model reference adaptive control architectures

ABSTRACT Model reference adaptive control (MRAC) offers mathematical and design tools to effectively cope with many challenges of real-world control problems such as exogenous disturbances, system uncertainties and degraded modes of operations. On the other hand, when faced with human-in-the-loop settings, these controllers can lead to unstable system trajectories in certain applications. To establish an understanding of stability limitations of MRAC architectures in the presence of humans, here a mathematical framework is developed whereby an MRAC is designed in conjunction with a class of linear human models including human reaction delays. This framework is then used to reveal, through stability analysis tools, the stability limit of the MRAC–human closed-loop system and the range of model parameters respecting this limit. An illustrative numerical example of an adaptive flight control application with a Neal–Smith pilot model is presented to demonstrate the effectiveness of developed approaches.

Large Deflection Aeroelasticity and Aeroelastic Lifting Line Theory for Examination of Aerodynamic Effects and Nonlinear Limit Cycle Oscillations

This paper investigates the effects of nonlinear large deflection bending on the aerodynamic performance and aeroelasticity of a high aspect ratio flexible wing. A nonlinear large deflection theory is developed for aeroelasticity to account for large deflection bending. An analysis is conducted to compare the nonlinear bending theory with the linear bending theory. The results show that the nonlinear bending theory is length-preserving whereas the linear bending theory causes a non-physical effect of lengthening of the wing structure under the no axial load condition. A modified lifting line theory is developed to compute the lift and drag coefficients of a wing structure undergoing a large bending deflection. The lift and and drag coefficients are more accurately estimated by the nonlinear bending theory due to its length-preserving property. The nonlinear bending theory yields a lower lift and higher induced drag than the linear bending theory. The nonlinear large deflection bending also can affect the structural dynamics of a high aspect ratio wing significantly. Limit cycle oscillations are a nonlinear phenomenon which arises from geometric nonlinearity and other sources of nonlinearities. Large deflection can manifest itself in limit cycle oscillations whereby linear flutter behaviors can result in an increase in the bending deflection up to a point where the geometric nonlinearity due to the large deflection begins to set in that results in limit cycle oscillations.

Development of an Integrated Nonlinear Aeroservoelastic Flight Dynamic Model of the NASA Generic Transport Model

This paper describes a recent development of an integrated fully coupled aeroservoelastic flight dynamic model of the NASA Generic Transport Model (GTM). The integrated model couples nonlinear flight dynamics to a nonlinear aeroelastic model of the GTM. The nonlinearity includes the coupling of the rigid-body aircraft states in the partial derivatives of the aeroelastic angle of attack. Aeroservoelastic modeling of the control surfaces which are modeled by the Variable Camber Continuous Trailing Edge Flap is also conducted. The R. T. Jones’ method is implemented to approximate unsteady aerodynamics. Simulations of the GTM are conducted with simulated continuous and discrete gust loads.

An Analysis of the Optimal Control Modification Method Applied to Flutter Suppression

Unlike standard Model Reference Adaptive Control (MRAC), Optimal Control Modification (OCM) has been shown to be a promising MRAC modification with robustness and analytical properties not present in other adaptive control methods. This paper presents an analysis of the OCM method, and how the asymptotic property of OCM is useful for analyzing and tuning the controller. We begin with a Lyapunov stability proof of an OCM controller having two adaptive gain terms, then the less conservative and easily analyzed OCM asymptotic property is presented. Two numerical examples are used to show how this property can accurately predict steady state stability and quantitative robustness in the presence of time delay, and relative to linear plant perturbations, and nominal Loop Transfer Recovery (LTR) tuning . The asymptotic property of the OCM controller is then used as an aid in tuning the controller applied to a large scale aeroservoelastic longitudinal aircraft model for flutter suppression. Control with OCM adaptive augmentation is shown to improve performance over that of the nominal non-adaptive controller when significant disparities exist between the controller/observer model and the true plant model.

Set-Theoretic Model Reference Adaptive Control of a Generic Transport Model

This paper illustrates an application of a recently developed set-theoretic model reference adaptive control architecture on a generic transport model developed by NASA. The settheoretic model reference adaptive control allows the system error bound between the state of an uncertain dynamical system and the state of a given reference model to be less than a-priori, user-defined worst-case performance bound. Thus, it has the capability to enforce strict performance guarantees to the adaptively controlled uncertain dynamical systems. Specifically, after designing set-theoretic adaptive controllers for both longitudinal and lateral-directional dynamics here, the efficacy of this architecture is illustrated on the NASA generic transport model.