Claudia P. Moreno

Model Reduction for Aeroservoelastic Systems

A model-reduction method for linear, parameter-varying systems based on parameter-varying balanced realizations is proposed for a body freedom flutter vehicle. A high-order linear, parameter-varying model with hundreds of states describes the coupling between the short period and first bending mode with additional structural bending and torsion modes that couple with the rigid body dynamics. However, these high-order state–space models result in a challenging control design, and hence a reduced-order linear, parameter-varying model is desired. The objective is to reduce the model state order across the flight envelope while retaining a common set of states in the linear, parameter-varying model. A reduced-order linear, parameter-varying model with tens of states is obtained by combining classical model reduction and parameter-varying balanced realizations reduction techniques. The resulting reduced-order model captures the unstable dynamics of the vehicle and is well suited for the synthesis of active flu...

Linear, Parameter Varying Model Reduction for Aeroservoelastic Systems

This paper applies a model reduction method for linear parameter-varying (LPV) systems based on parameter-varying balanced realization techniques to a body freedom utter (BFF) vehicle. The BFF vehicle has a coupled short period and rst bending mode with additional structural bending and torsion modes that couple with the rigid body dynamics. These models describe the BFF vehicle dynamics with considerable accuracy, but result in high-order state space models which make controller design extremely dicult. Hence, reduced order models for control synthesis are generated by retaining a common set of states across the ight envelope. Initially the full order BFF models of 148 states are reduced to 43 states using standard truncation and residualisation techniques. The application of balanced realization techniques at individual point designs result in 20 state models. Unfortunately, the application of balanced realization techniques at individual operating conditions results in dierent states being eliminated at each operating condition. The objective of LPV model reduction is to further reduce the model state order across the ight envelope while retaining consistent states in the LPV model. The resulting reduced order LPV models with 26 states capture the dynamics of interest and can be used in the synthesis of active utter suppression controllers.

Structural model identification of a small flexible aircraft

The system identification of a light-weight, high-aspect ratio wing is presented. Experimental data is obtained from a ground vibration test. The input signals are sine sweep wave forces and the outputs are the corresponding acceleration responses of the aircraft. Subspace algorithms are used to estimate a state-space model of the aircraft. Minimization of the model prediction error is performed to fit the frequency response data. As result, the estimated model identifies six structural modes between 5 Hz and 30 Hz.

Design of an optimal tuned mass damper for a system with parametric uncertainty

Structural control is becoming an attractive alternative for enhanced performance of civil engineering structures subject to seismic and wind loads. However, in order to guarantee stability and performance of structures when implemented with a passive or active control technique, there is a need to include information of uncertainty in the structural models due to the fact that civil engineering structures are time variant and nonlinear. These variations in the structure are often due to parameters such as variable live loads and inelastic behavior and, in cases, may be modeled as parametric uncertainty. The design of an optimal tuned mass damper (TMD) for a one degree-of-freedom (SDOF) system with parametric uncertainty is presented in this paper. The optimization of the connection between the absorber and the primary structure is cast as a constant feedback problem which is solved using structured singular value, μ, synthesis with D-K iteration and decentralized H∞ design. Results are presented of the TMD that minimize the harmonic response of the primary structure represented by a set of systems within an uncertainty set.

Updating a finite element based structural model of a small flexible aircraft

The generation of a finite element based structural model of a small, flexible unmanned aircraft is presented. The paper focuses on obtaining a simple model suitable for control design based on a two step procedure. In an initial step, static and dynamic tests of the wings are conducted. These experiments give first estimates of the material properties (e.g., stiffness) of the aircraft. A finite element model consisting of simple beam elements is constructed based on these first estimates. In the next step, the modal data of the aircraft is extracted from a ground vibration test. The initial finite element model is then updated using this modal data. An optimization problem is proposed to minimize the difference in the modal properties, i.e. the modal frequencies and mode shapes, between the model and the experimental data. The free parameters of the optimization are chosen based on physical insights of the system. The resulting finite element model closely matches the experimental data both in terms of modal properties as well as input/output behavior.

Low cost development of a nonlinear simulation for a flexible uninhabited air vehicle

The development of a nonlinear simulation environment for an uninhabited air vehicle with a flexible airframe is presented. Simple, yet efficient testing procedures are employed to estimate the physical properties of the aircraft. The aerodynamic forces and moments are obtained using a doublet lattice method. The interaction between structural dynamics and aerodynamics is given special attention from a modeling standpoint. The simulation is finally integrated into the existing simulation infrastructure maintained by the research group. A modular approach is emphasized in the simulation build-up, which allows for easy switching between models.

Actuator and sensor selection for robust control of aeroservoelastic systems

This paper proposes an approach for actuator and sensor selection for a small flexible aircraft. The approach is based on the synthesis of robust controllers accounting for model uncertainty. The objective is to find, out of a finite set of actuator/sensor configurations available in the aircraft, the best configuration that provides sufficient robustness and desired performance. The results show that the ability to stabilize and achieve performance objectives of aeroservoelastic systems is highly dependent on the selection of actuators and sensors for feedback control.

Robust Aeroservoelastic Control Utilizing Physics-Based Aerodynamic Sensing

The paper describes the design of aeroservoelastic controllers using H1 and LPV control design techniques for a Body Freedom Flutter aircraft. The controllers are compared in the frequency and time domain The LPV controller does not achieve the level of performance of the individual H1 controllers, though the performance achieves the desired objectives. The similarities and difference between the designs are discussed. The need for improved performance and reduced operating costs has led modern aircraft designers to adopt lightweight, high aspect ratio wings. However, the high flexibility and significant deformation in flight exhibited by these aircraft increase the interaction between the rigid body and structural dynamics modes resulting in Body Freedom Flutter. This phenomenon occurs as the aircraft short period mode frequency increases with airspeed and comes close to a wing vibration mode. This lead to poor handling qualities and may even generate dynamics instability. Hence, an integrated active approach to flight control and flutter suppression is required to meet the desired handling quality performance without compromise structural weight and flight envelope. This paper presents the design ofHinf and linear, parameter-varying controller for a Body Freedom Flutter (BFF) vehicle developed by the Air Force Research Laboratory to demonstrate active aeroelastic control technologies. The vehicle is a high aspect ratio flying wing with light weight airfoil. The aircraft configuration with the location of accelerometers and control surfaces for flutter suppression is presented in the Figure 1. The aeroservoelastic (ASE) model of the BFF vehicle was assembled using MSC/NASTRAN. A Ground Vibration Test was performed to validate the structural model and six critical modes were found. Table 1 lists the mode shapes and frequency values of the structural model. 1‐3

Flight Dynamics Modeling of a Body Freedom Flutter Vehicle for Multidisciplinary Analyses

Integrated flight dynamic models play an essential role in all aircraft design phases. Examples are flight loads analysis for sizing of the structure, design of control laws, as well as design and analysis of missions. For these purposes, DLR has developed a robust, quick and unified process for generating, pre-processing and automatically integrating aircraft models. The process is called DLR Aircraft Model Integration Process (DAMIP) and is able to draw from a variety of different (best available) data sources. The DAMIP proce- dure is based on an unified environment, allowing aircraft modeling projects to be set-up in an easy and comfortable fashion. After this, the individual steps can be performed automatically, making it very suitable for the use in multidisciplinary design analysis and optimization loops. This paper outlines and demonstrates the DAMIP process as applied to the Body Freedom Flutter (BFF) vehicle that is currently studied and in-use at the De- partment of Aerospace Engineering at the University of Minnesota. In order to validate the integrated models the modal basis of the BFF vehicle is corrected by data obtained from ground vibration test (GVT). Linear state-space models are then generated to feed linear parameter-varying (LPV) system approaches and perform a flutter analysis by inspecting stability of the system matrices. The results are compared to those of the P-K Method analysis performed by Lockheed Martin Aeronautics. To demonstrate the flexibility of DAMIP, nonlinear models were generated in the equation-based, object-oriented Model- ica language and exported as S-functions to be used in the Matlab/Simulink simulation environment.

Close-loop stabilization of a flexible wing aircraft

The design of the airframe of an aircraft is constrained due to aeroelastic effects (generally related to the wings) that induce flexible modes on the structure, and may lead to structural instability. This paper addresses the problem of active mode stabilization in an aircraft with flexible wings. The main objective of closed-loop control is to enlarge the allowable flight envelope by stabilizing flexible modes that become unstable after a certain airspeed is exceeded. The nominal full-order (FO) model has a very large state dimension and hence the controller is designed using a reduced order (RO) model. This paper offers an analysis of the trade-offs present when designing controllers for systems under the premise of large order model reductions. Simulation results are provided using a reliable high order linear model.