Ilkay Yavrucuk

Envelope Protection for Autonomous Unmanned Aerial Vehicles

This paper describes the design, development, and testing of an automatic envelope protection system as implemented on Georgia Institute of Technology’s unmanned helicopter GTMax. The envelope protection system makes use of online-learning adaptive neural networks to generate online dynamic models, which are used to estimate limits on controller commands. The system provides command capability up to the limit boundaries while preventing envelope exceedance. Simulation and flight-test results are provided for load factor and rotor stall limit protection during aggressive maneuvering.

A low cost flight simulator using virtual reality tools

A helicopter simulator is built using Head-Mount-Displays (HMD) and Data Gloves with trackers to test the viability of virtual reality tools in low-cost flight simulation. The simulator uses FlightGear as its simulation environment and an in-house developed UH-1H helicopter flight dynamics model. Running several clone simulations on different computers allowed stereo imaging on the HMD and instructor station applications. Data Gloves with trackers enabled interaction with the virtual cockpit.

Control algorithm and flight simulation integration using the open control platform for unmanned aerial vehicles

In order for Unmanned Aerial Vehicles (UAVs) to exhibit increasing degrees of autonomy; heterogeneous control system software needs to be able to collaborate and reconfigure to varying mission conditions. Currently this ability is very limited due to inadequate software architectures on which the control systems are implemented. This paper describes an integration platform that adopts an open systems approach to integrating heterogeneous control algorithms. This platform was applied to real-time piloted and unpiloted simulations of a helicopter UAV while testing the performance of an adaptive controller as well as the ability to reconfigure during a main rotor collective actuator failure. Results indicate that the chosen architecture can greatly increase the ability to integrate heterogeneous components in a seamless fashion into a collaborating set of resources that achieve the desired mission functionality. This paper describes the integration of flight modeling and visualization with control algorithms.

Simulation and Flight Control of a Tilt Duct UAV

Tilt duct VTOL UAV concept is presented. The equations of motion are given and, trim and simulation code is described. Trim flight conditi ons are given for hover, cruise and forward flight cases. A two loop SDRE control is propos ed and explained. The blended inverse control allocation algorithm is used for allocati ng controllers during the transition flight phase, where there are redundant controls. Sim ulation results during transition phase are presented, and the success of the controller as we ll as the allocation algorithm is demonstrated. Nomenclature ij I = mass moments of inertias

Application of Software Enabled Control Technologies to a Full-Scale Unmanned Helicopter

This paper presents a control architecture designed to accommodate a selection of modern control algorithms on a full-scale rotary-wing, unmanned aerial vehicle. The architecture integrates a visual landing system, two path planners, a flight envelope protection algorithm, and two low-level flight controllers that were developed independently by six agencies in academia and industry. A newly developed vehicle model and an exportable simulation environment were assembled in an open control infrastructure to expedite the algorithm development. The collaboration resulted in successful flight testing of the architecture and multiple control algorithms on Boeing’s Renegade Unmanned Aerial Vehicle, a derivative of the Robinson R22. The aircraft successfully switched from a conventional flight controller to an adaptive neural network flight controller on four occasions making it the largest helicopter to operate under adaptive neural network flight control.

Simulation of reconfigurable Heli-UAV's using main rotor RPM control in failure modes

This paper presents modeling, analysis and simulation evaluations for using main rotor RPM as a substitute control in case of partial failure of main rotor collective control of a Helicopter Uninhabited Aerial Vehicle (Heli-UAV). It is shotin that the use of main rotor RPM variations combined with advanced adaptive control architectures can successfully compensate for partial loss of main rotor collective control. The overall concept is illustrated using simulation results for an example failure scenario. Comparison plots are given to illustrate differences with and without the RPM Control option as well as the nominal flying case. Also, coupling effects of RPM changes on other control channels are illustrated.

Concurrent Learning Enabled Adaptive Limit Detection for Active Pilot Cueing

Neural-network-based adaptive dynamic models are commonly used to estimate allowable control travel and the proximity to a limiting flight condition in the design of advanced envelope protection algorithms for fly-by-wire aircraft. In this paper, linear models are compensated with adaptive neural networks, which use instantaneous sensor data as well as past flight history information for concurrent learning. A law for collecting appropriate training data into the history stack is established. It is observed that using the proposed time history data for online neural network training provides more accurate dynamic trim and control limit predictions compared to using instantaneous sensor data only. Simulation results for a fixed-wing aircraft during maneuvers show comparisons between the different adaptation schemes.

Simulation Evaluation of a Reconfigurable Flight Controller of a Heli-UAV for Extreme Maneuvers

Recent advances in software engineering, computer processing and control engineering are creating opportunities for advancing the state-of-the-art in Uninhabited Aerial Vehicle (UAV) operations. Specifically, in order to exploit the full potential of UAVs, they are required to operate in confined air space such as in between buildings close to obstacles, and they are required to perform extreme maneuvers during such operations. A flight controller configured for normal mode of operation may not be effective for control of the vehicle during extreme maneuvers without some sort of control reconfiguration. This paper presents simulation evaluation of a mode transitioning and control reconfiguration strategy based on fuzzy logic for a helicopter UAV in transitioning from a nominal forward speed flight mode to a barrel roll mode and back.

Panel-Method-Based Path Planning and Collaborative Target Tracking for Swarming Micro Air Vehicles

This paper presents an application of the potential field panel method commonly used in aerodynamics analysis to obtain streamlinelike trajectories and use them for path planning and collaborative target tracking for swarming micro air vehicles in an urban environment filled with complex shaped buildings and other architectural structures. In addition, we introduce a performance matching technique that relates the fluid velocities, which are obtained as a partof the panel method solution, to vehicle velocities along each trajectory. The approach is further extended to track moving targets yet avoid obstacles and collision between the vehicles. Because of the inherent nature of streamlines, obstacle avoidance is automatically guaranteed. To make the micro air vehicles follow and track a moving target, dynamically changing streamline patterns are calculated for each and every one of the micro air vehicles within a swarm. To prevent vehicle-to-vehicle collisions, each micro air vehicle is represented using a point source singularity element within the potential field. The simulation results are quite encouraging, in the sense that micro air vehicle swarms quickly locate and track the assigned targetin an environment filled with complex-shaped structures while avoiding obstacles and collisions among themselves. One benefit of the method is that the trajectory computations can be relatively fast and even have the potential to be applied in real time, depending on the number and complexity of the urban structures.

Gimbal angle restricted control moment gyroscope clusters

Momentum envelopes for a cluster of four CMGs in pyramid mounting are obtained. The envelopes when gimbal travel is limited to ±90° are also presented. CMG steering simulations using Moore Penrose pseudo inverse as well as blended inverse are presented, and success of the pre planned blended inverse in avoiding gimbal angle limits is demonstrated. Also given is a successful satellite slew maneuver example using blended inverse, showing the completion of the maneuver without violating gimbal angle travel restrictions.