Aircraft System Identification from Multisine Inputs and Frequency Responses

A frequency-domain approach is described for estimating parameters, such as stability and control derivatives, in aircraft flight dynamic models from measured input and output data. The approach uses orthogonal phase-optimized multisines for moving the aircraft control effectors, Fourier analysis for computing multiple-input multiple-output frequency responses, and a maximum likelihood estimator called frequency response error (FRE) for determining values and uncertainties for the model parameters. The approach is demonstrated using flight test data for two subscale airplanes: the T-2 generic transport model and the X-56A aeroelastic demonstrator. Results and comparisons with the output-error method indicated that the approach produced accurate estimates of stability and control derivatives and their uncertainties from flight test data

Centrifugally Stiffened Rotor: Eternal Flight as the Solution for 'X': NIAC Phase I Final Report

Flight has always captured man's imagination. This is evidenced by the great variety of aerial vehicles that exist today. Everything from fixed-wing to rotorcraft; satellites to spaceships;mono-wing to quadrotor. However, despite the wide variety of flying vehicles, not one of them has attained eternal flight. Accomplishing this feat is one of the great challenges still facing the aviation community. Motivation Achieving eternal flight opens the doors to atmospheric satellites. Existing satellites have a great number of capabilities that enrich our lives; however,their distance from the surface of the earth precludes certain types of transmission capabilities. Once eternal flight is achieved, that vehicle can serve the same role as ordinary satellites, but its close proximity will allow for real time two way communications,like wireless broadband internet. And with active controls, atmospheric satellites would not be constrained to geosynchronous orbits, like our existing satellite technology. Many projects are under way to achieve this goal;however, most of these research efforts follow the same design methodology, and have exhausted the limits of this particular design. This concept introduces a completely new aerial vehicle structure,which uses the best features of fixed-wing and rotorcraft designs. Combining the best features of different classes of aircraft, expands the capabilities beyond what either one can achieve on its own

Advanced Concept Modeling

Advanced Concepts Modeling software validation, analysis, and design. This was a National Institute of Aerospace contract with a lot of pieces. Efforts ranged from software development and validation for structures and aerodynamics, through flight control development, and aeropropulsive analysis, to UAV piloting services

An Evaluation on Wind Energy Potential using Multi-Objective Optimization-based Non-dominated Sorting Genetic Algorithm III

Wind energy is an abundant renewable energy resource that is extensively used worldwide in recent years. The present work proposes a new Multi-Objective Optimization (MOO) based genetic algorithm (GA) model for a wind energy system. The proposed algorithm consists of non-dominated sorting which focuses to maximize the power extraction of the wind turbine and the lifetime of the battery. Also, the performance characteristics of the wind turbine and battery energy storage system (BESS) are analyzed specifically torque, current, voltage, state of charge (SOC), and internal resistance. The complete analysis is carried out in the MATLAB/Simulink platform. The simulated results are compared with existing optimization techniques such as single-objective, multi-objective, and non-dominating sorting GA II (Genetic Algorithm-II). From the observed results, the NSGA III optimization algorithm offers superior performance notably higher turbine power output with higher torque rate, lower speed variation, and lesser degradation rate of the battery. This result attested to the fact that the proposed optimization tool can extract a higher rate of power from a self-excited induction generator (SEIG) when compared with a conventional optimization tool.publishedVersio

Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands

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