Design and simulation of advanced fault tolerant flight control schemes

This research effort describes the design and simulation of a distributed Neural Network (NN) based fault tolerant flight control scheme and the interface of the scheme within a simulation/visualization environment. The goal of the fault tolerant flight control scheme is to recover an aircraft from failures to its sensors or actuators. A commercially available simulation package, Aviator Visual Design Simulator (AVDS), was used for the purpose of simulation and visualization of the aircraft dynamics and the performance of the control schemes.;For the purpose of the sensor failure detection, identification and accommodation (SFDIA) task, it is assumed that the pitch, roll and yaw rate gyros onboard are without physical redundancy. The task is accomplished through the use of a Main Neural Network (MNN) and a set of three De-Centralized Neural Networks (DNNs), providing analytical redundancy for the pitch, roll and yaw gyros. The purpose of the MNN is to detect a sensor failure while the purpose of the DNNs is to identify the failed sensor and then to provide failure accommodation. The actuator failure detection, identification and accommodation (AFDIA) scheme also features the MNN, for detection of actuator failures, along with three Neural Network Controllers (NNCs) for providing the compensating control surface deflections to neutralize the failure induced pitching, rolling and yawing moments. All NNs continue to train on-line, in addition to an offline trained baseline network structure, using the Extended Back-Propagation Algorithm (EBPA), with the flight data provided by the AVDS simulation package.;The above mentioned adaptive flight control schemes have been traditionally implemented sequentially on a single computer. This research addresses the implementation of these fault tolerant flight control schemes on parallel and distributed computer architectures, using Berkeley Software Distribution (BSD) sockets and Message Passing Interface (MPI) for inter-process communication

Autonomous Close Formation Flight Control with Fixed Wing and Quadrotor Test Beds

Autonomous formation flight is a key approach for reducing energy cost and managing traffic in future high density airspace. The use of Unmanned Aerial Vehicles (UAVs) has allowed low-budget and low-risk validation of autonomous formation flight concepts. This paper discusses the implementation and flight testing of nonlinear dynamic inversion (NLDI) controllers for close formation flight (CFF) using two distinct UAV platforms: a set of fixed wing aircraft named “Phastball” and a set of quadrotors named “NEO.” Experimental results show that autonomous CFF with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned Phastball research aircraft. Simulations of the quadrotor flight also validate the design of the NLDI controller for the NEO quadrotors

Flights of a Multirotor UAS with Structural Faults: Failures on Composite Propeller(s)

Data acquired from several flights of a custom-fabricated Hexacopter Unmanned Aerial System (UAS) with composite structure (carbon fiber arms and central hub) and composite (carbon fiber) propellers are described in this article. The Hexacopter was assembled from a commercially available kit (Tarot 690) and flown in manual and autonomous modes. Takeoffs and landings were under manual control and the bulk of the flight tests was conducted with the Hexacopter in a “position hold” mode. All flights were flown within the UAS flight cage at Parks College of Engineering, Aviation and Technology at Saint Louis University for approximately 5 min each. Several failure conditions (different types, artificially induced) on the composite (carbon fiber) propellers were tested, including failures on up to two propellers. The dataset described in this article contains flight data from the onboard flight controller (Pixhawk) as well as three accelerometers, each with three axes, mounted on the arms of the Hexacopter UAS. The data are included as supplemental material

Design of anechoic chamber instrumentation and data acquisition module for testing and analysis of the CTHA

The backbone of wireless communication is an antenna, a device that converts electromagnetic energy to electric energy and vice versa, to transmit and receive the signals. The effectiveness of a communication system depends largely on the effectiveness of the antenna used in them. The effectiveness of an antenna is characterized by its electromagnetic field. Methods to characterize the field of an antenna include testing them on outdoor test ranges or in enclosures insulated against electromagnetic radiation, called anechoic chambers. The objective of this work is to design and build an automated data acquisition system to map the field of physically small antennas such as a Contrawound Toroidal Helical Antenna (CTHA), placed inside an anechoic chamber built and maintained by the Center for Industrial Research Applications (CIRA), West Virginia University. Two antennas, a dipole in the transmitting mode and the CTHA, the antenna under test, in the receiving mode are used in the tests. The automated setup includes a rotator for mounting the antenna, a signal generator and a spectrum analyzer to analyze the signals from the receiving antenna. The rotator, signal generator and the spectrum analyzer are controlled remotely by a Visual Basic program running on a central control computer. The acquired data is presented in a graphical form, representing the field around the antenna

Autonomous “Figure-8” Flights of a Quadcopter: Experimental Datasets

This article describes the data acquired from multiple flights of a custom-built quadcopter. The Quadcopter was programmed to fly a pre-defined “Figure-8” flight path, at a constant altitude. The data set includes flights with a varying number of waypoints (10 and 15 waypoints in each lobe of the “Figure-8”) and at two different velocities (1.5 and 2.5 m/s). The data also contains information on the output of the flight controller in terms of the Pulse Width Modulation (PWM) signals to each of the four Electronic Speed Controllers (ESC) driving the motors, the recorded outputs of the Inertial Measurement Unit (linear accelerations ax, ay, az and angular velocities p, q, r), GPS data (Latitude, Longitude, altitude, Horizontal Dilution of Precision (HDOP) and Vertical Dilution of Precision (VDOP). The data are included as Supplemental Material

Evaluation of a Baseline Controller for Autonomous “Figure-8” Flights of a Morphing Geometry Quadcopter: Flight Performance

This article describes the design, fabrication, and flight test evaluation of a morphing geometry quadcopter capable of changing its intersection angle in-flight. The experiments were conducted at the Aircraft Computational and Resource Aware Fault Tolerance (AirCRAFT) Lab, Parks College of Engineering, Aviation and Technology at Saint Louis University, St. Louis, MO. The flight test matrix included flights in a “Figure-8” trajectory in two different morphing configurations (21° and 27°), as well as the nominal geometry configuration, two different flight velocities (1.5 m/s and 2.5 m/s), two different number of waypoints, and in three planes—horizontal, inclined, and double inclined. All the experiments were conducted using standard, off-the-shelf flight controller (Pixhawk) and autopilot firmware. Simulations of the morphed geometry indicate a reduction in pitch damping (42% for 21° morphing and 57.3% for 27° morphing) and roll damping (63.5% for 21° morphing and 65% for 27° morphing). Flight tests also demonstrated that the dynamic stability in roll and pitch dynamics were reduced, but the quadcopter was still stable under morphed geometry conditions. Morphed geometry also has an effect on the flight performance—with a higher number of waypoints (30) and higher velocity (2.5 m/s), the roll dynamics performed better as compared to the lower waypoints and lower velocity condition. The yaw dynamics remained consistent through all the flight conditions, and were not significantly affected by asymmetrical morphing of the quadcopter geometry. We also determined that higher waypoint and flight velocity conditions led to a small performance improvement in tracking the desired trajectory as well