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A Stagnation Point Actuator is used to control the lateral dynamics of vortices generated over a sharp-pointed forebody, at high angles of attack, and the resulting rolling moment is studied. Effective roll control is demonstrated, including the ability to suppress the wing rock phenomenon. Piecewise-linear transfer functions are developed from experimental data for the changes in roll moment and pressure difference with actuator frequency content. These transfer functions are reduced to compact form in the frequency domain, and then to a time-domain model using 2 gains and 2 time scales. The roll response is classified according to angle of attack range. Some long time scales are observed in the surface pressure, velocity field and rolling moment, making the response relatively insensitive to speed. Thus over substantial speed ranges, linear transfer functions are shown to effectively describe the roll response to motion of the Stagnation Point Actuator.

Neural network augmented model inversion control is used to provide a civilian tilt-rotor aircraft with consistent response characteristics throughout its operating envelope, including conversion flight. The implemented response types are Attitude Command Attitude Hold in the longitudinal channel, and Rate Command Attitude Hold about the roll and yaw axes. This article describes the augmentation in the roll channel and the augmentation for the yaw motion including Heading Hold at low airspeeds and automatic Turn Coordination at cruise flight. Conventional methods require extensive gain scheduling with tilt-rotor nacelle angle and airspeed. A control architecture is developed that can alleviate this requirement and thus has the potential to reduce development time. It also facilitates the implementation of desired handling qualities, and permits compensation for partial failures.

This paper critically evaluates the use of Neural Networks (NNs) as metamodels for design applications. The specifics of implementing a NN approach are researched and discussed, including the type and architecture appropriate for design-related tasks, the processes of collecting training and validation data, and training the network, resulting in a sound process, which is described. This approach is then contrasted to the Response Surface Methodology (RSM). As illustrative problems, two equations to be approximated and a real-world problem from a Stability and Controls scenario, where it is desirable to predict the static longitudinal stability for a High Speed Civil Transport (HSCT) at takeoff, are presented. This research examines Response Surface Equations (RSEs) as Taylor series approximations, and explains their high performance as a proven approach to approximate functions that are known to be quadratic or near quadratic in nature.

Test methods and data acquisition system specifications are described for measurements of the energy consumption of the control system of a servo-pump continuously variable transmission (CVT). Dynamic measurements of the power consumption of the servo-pump CVT control system show that the control system draws approximately 18.9 W-hrs of electrical energy over the HWFET cycle and 13.6 W-hrs over the 505 cycle. Sample results are presented of the dynamic power consumption of the servo-pump system under drive cycle conditions. Steady state measurements of the control power draw of the servo-pump CVT show a peak power consumption of 271 W, including lubrication power. The drive-cycle averaged and steady state energy consumption of the servo-pump CVT are compared to conventional CVT pump technologies.

The present use of the carburetor to supply fuel to the Otto cycle engine has placed it in a difficult competitive position with the diesel engine, which has successfully operated with a fuel injection system. The purpose of this study was to consider the feasibility of utilizing a low pressure injection system for the Otto cycle engine. The proposed design is discussed in detail. As the author points out, this system will allow design changes in the engine that would be impossible if the carburetor were retained, and thus considerable improvement in performance and efficiency can be realized for the Otto cycle engine.

A technique is proposed for examining complex behaviors in the “pilot - vehicle - operational conditions” system using an autonomous situational model of flight. The goal is to identify potentially critical flight situations in the system behavior early in the design process. An exhaustive set of flight scenarios can be constructed and modeled on a computer by the designer in accordance with test certification requirements or other inputs. Distinguishing features of the technique include the autonomy of experimentation (the pilot and a flight simulator are not involved) and easy planning and quick modeling of complex multi-factor flight cases. An example of mapping airworthiness requirements into formal scenarios is presented. Simulation results for various flight situations and aircraft types are also demonstrated.

A hybrid electric vehicle (HEV) simulation has been developed for an electric-assist parallel configuration vehicle, at the University of Tennessee, Knoxville. The model was developed in MATLAB/SIMULINK using ADVISOR, a HEV simulation model developed by the National Renewable Energy Laboratory. The Neon simulation model implements a power control strategy using throttle position as the primary input. It incorporates other features of HEV power control such as battery regeneration and regenerative braking. A practical way of battery modeling is incorporated into this model. The model also simulates the vehicle operation as a pure electric vehicle (EV) or as a conventional vehicle (heat engine only). By using the Neon model, the performance of the vehicle has been analyzed using parametric analysis of the vehicle components and power control parameters. Recommendations are given for improving the design based on the simulation results.

The ultimate goal of knowledge-based aircraft design, pilot training and flight operations is to make flight safety an inherent, built-in feature of the flight vehicle, such as its aerodynamics, strength, economics and comfort are. Individual flight accidents and incidents may vary in terms of quantitative characteristics, circumstances, and other external details. However, their cause-and-effect patterns often reveal invariant structure or essential causal chains which may re-occur in the future for the same or other vehicle types. The identification of invariant logical patterns from flight accident reports, time-histories and other data sources is very important for enhancing flight safety at the level of the ‘pilot - vehicle -operational conditions’ system. The objective of this research project was to develop and assess a method for ‘mining’ knowledge of typical cause-and-effect patterns from flight accidents and incidents.

An intelligent connected vehicle (ICV) swarm system that includes N vehicles is considered. Based on the special properties of potential functions, a kinematic model describing the swarm performances is proposed, which allows all vehicles to enclose the tracking target and show both tracking and formation characteristics. Treating the performances as the desired constraints, the analytical form of constraint forces can be obtained inspired by the Udwadia-Kalaba approaches. A special approach of uncertainty decomposition to deal with uncertain interferences is proposed, and a switching-type robust control method is addressed for each vehicle agent in the swarm system. The features and validity of the addressed control are demonstrated in the numerical simulations.