The fuel efficiency of future aircraft can be improved by reducing the weight and structure and by increasing the wingspan. This makes the aircraft structure more flexible and results in increased aeroservoelastic (ASE) effects. The use of active control systems to suppress ASE effects is an important aspect for future flight control systems. The basis of active control system design is an appropriate control oriented model, usually given in the linear parameter-varying (LPV) framework. The ASE model is based on the integration of aerodynamics, structural dynamics and flight dynamics. These subsystems can be developed separately and combined to form the ASE model. The dynamic order of such ASE models is usually too large for control synthesis and implementation. Thus, model order reduction is required. However, model order reduction of LPV systems can still lead to challenges. The aim of the paper is to overcome this reduction step by using a "bottom-up" modeling approach. The main idea is to use low order, simple subsystems and/or reduce them before integrating them into the nonlinear model. Therefore, a low order control oriented model is created that captures the key ASE dynamics of the aircraft. An important benefit of this modeling approach is that the physical meaning of the states is retained. The specific flexible aircraft example is the mini MUTT (Multi Utility Technology Testbed) vehicle. The bottom-up modeling approach, by reducing the linear structural dynamics and the parameter dependent aerodynamics subsystems, resulted in a 33 state low order nonlinear model (LOM). The nonlinear model is then linearized about a family of "trim points" by Jacobian linearization leading to a grid based LPV model. A full order model (FOM) is developed in order to evaluate the accuracy of the 33 state LOM. The FOM is developed in the same way as the LOM. However, the subsystems are not reduced in this case, leading to a 97 states model. The accuracy of the low order model is confirmed by evaluating the ν-gap metric with respect to the full order model and by time domain simulations.

An unsteady aerodynamics model of a flexible unmanned air vehicle is presented in this paper. The unsteady aerodynamics results from structural vibrations of the flexible airframe which affect the airflow around it. The doublet lattice method, which is a potential flow based panel method, is used for obtaining the basic unsteady aerodynamics model. It gives the pressure distribution on a lifting surface harmonically oscillating in steady flow. The basic concepts, underlying assumptions and approximations of the method are discussed. The extensive post processing which is done for the model obtained from the doublet lattice method is also described. The aerodynamic model is first transformed into suitable coordinates to account for structural vibrations effects. A rational function fitting is then carried out to obtain the final model which is suitable for time domain analysis. We use these methods to obtain an unsteady aerodynamics model of the Body Freedom Flutter vehicle, a flexible test bed aircraft. The results of this application are discussed. The final model is used for developing a nonlinear simulation for the flexible aircraft which is capable of simulating phenomena such as flutter and is important for integrated control law synthesis for the aircraft. The software for DLM as well as the post processing tools are made available as an open source research tool for aeroelastic systems research. Nomenclaturē w Component of flow velocity perpendicular to a surface, normalized by freestream airspeed p Lifting pressure vector normalized by freestream dynamic pressure ω Oscillation frequency (rad/s) k Reduced frequency AIC Aerodynamics Influence Coefficients Matrix V Free stream airspeed (m/s) η Structural deflections in modal coordinates T as Transformation matrix for obtaining aerodynamics in modal coordinates Φ Mode shapes Q(k) Generalized aerodynamics matrix (GAM), function of reduced frequency * Graduate Student, AIAA Student Member

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