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Failures of the aircraft control system sensors can cause both deterioration of stability and controllability characteristics and the inability of safe automatic control. It is necessary to detect and isolate such failures to determine the time and place of their occurrence in order to disable failed sensors or to diagnose them subsequently for reconfiguration during the flight. The direct use of traditional parametric approaches for sensors health monitoring by using their mathematical models is impossible due to the lack of data about the true information input signals received by their sensitive elements. This leads to the necessity of solving the problem of modeling the aircraft flight dynamics with a high level of uncertainties, which makes it difficult to utilize the functional control methods and necessitate the use of excessive sensor hardware redundancy. Well-known nonparametric methods either require a priori knowledge base, preliminary training or long-term tuning on a large volume of real flight data or have low selective sensitivity for reliable detection of failed sensors. In this work, the original nonparametric criterion for detecting and isolating sensors failures is derived. Its sensitivity is analyzed by using a complete nonlinear mathematical model of aircraft flight dynamics with a regular flight control system. The theoretical value and the criterion sensitivity coefficients are determined. The formula for the automatic evaluation of the float criterion threshold value is given. A high convergence of the results with theoretical ones is shown. This makes it possible to use the obtained criterion not only for the instant detection and isolation of sensors failures, but also for preliminary diagnostics of their quantitative characteristics.

Data-driven algorithms are developed to fully automate sensor fault detection in systems governed by underlying physics, with a particular focus on the flight test setting. The proposed machine lea...

The INS/GNSS integration is the commonly used technique for hypersonic vehicle navigation. However, owing to the complicated flight dynamics with high maneuverability and large flight envelope, the dynamic model of INS/GNSS integration inevitably exists errors which degrades the navigation performance of a hypersonic vehicle seriously. In this paper, a new model predictive based unscented Kalman filter (MP-UKF) is proposed to address this problem. The MP-UKF employs the concept of model predictive filter for the establishment of a dynamic model error estimator, and it subsequently compensate the model error estimation to UKF for nonlinear state estimation. Since the MP-UKF could predict the dynamic model error persistently and correct the filtering procedure of UKF online, it improves the UKF adaptiveness and is promising for the performance enhancement of INS/GNSS integration for hypersonic vehicle navigation. Simulation results and comparison analysis have been conducted to demonstrate the effectiveness of the proposed method.

People who live in low-income and hard-to-reach regions are usually the most affected ones by high incidences of arboviral diseases, increasing morbidity and mortality rates, and public health costs. We present the modeling of hardware and software components of an unmanned aerial vehicle (UAV) system by mathematical tools, focusing on monitoring foci of arboviral diseases transmitted by Aedes aegypti mosquito, e.g., Zika, Chikungunya, and Dengue. We used restriction equations and the colored Petri nets formal modeling language to represent the flight dynamics and the software components of the system, respectively. We evaluated the specification of desired behaviors of the monitoring system using simulations and the model checking technique. The results showed the completeness and correctness of the specification. The design of such a system is challenging due to the potential risks to people and the environment. Therefore, this study provides insights into the development of an UAV system for such an application scenario. The monitoring system has the potential of improving the efficiency in identifying foci of arboviral diseases.

The cause of the rapid growth and enhancement in the dynamics of unmanned aerial vehicles (UAVs) is due to its vast utilization in every-day application. The major advantage of UAVs is no risk of human life with secure and suitable surveillance. The UAV facilitates in live video streaming and wide aerial coverage for monitoring. In this project, a type of UAV named quadcopter has been developed. The work mainly consists of design of the quadcopter frame, interfacing of the brushless DC motors and bluetooth module with the microcontroller, and adjustment of the roll, pitch, and yaw for keeping the smooth flight dynamics by flight controller board containing MEMS sensors, i.e., gyroscope, accelerometer, magnetometer, and pressure sensors. The repeated simulation and testing has been carried out in MATLAB for the mathematical modeling of the dynamics of the system, i.e., Euler method for solving differential equation for finding system states, computation of the rotation matrix R and functions to convert from an angular velocity vector w to the derivatives of roll, pitch, and yaw. The improvement in the parameters of the flight dynamics and removing the errors to gain stability in the frame are the main core issues which have been achieved by the several iterations. A closed-loop control system, i.e., PID controller, has been simulated and carefully designed for stabilizing the actual angle from the sensors and desired angle from the pilot. The reduced error rate of 0.05 degrees after every 10 s was achieved.

The emergence of agricultural land use change creates a number of challenges that insect pollinators, such as eusocial bees, must overcome. Resultant fragmentation and loss of suitable foraging habitats, combined with pesticide exposure, may increase demands on foraging, specifically the ability to reach resources under such stress. Understanding the effect that pesticides have on flight performance is therefore vital if we are to assess colony success in these changing landscapes. Neonicotinoids are one of the most widely used classes of pesticide across the globe, and exposure to bees has been associated with reduced foraging efficiency and homing ability. One explanation for these effects could be that elements of flight are being affected, but apart from a couple of studies on the honeybee, this has scarcely been tested. Here we used flight mills to investigate how exposure to a field realistic (10ppb) acute dose of imidacloprid affected flight performance of a wild insect pollinator - the bumblebee,Bombus terrestris audax. Intriguingly, intial observations showed exposed workers flew at a significantly higher velocity over the first ¾ km of flight. This apparent hyperactivity, however, may have a cost as exposed workers showed reduced flight distance and duration to around a third of what control workers were capable of achieving. Given that bumblebees are central place foragers, impairment to flight endurance could translate to a decline in potential forage area, decreasing the abundance, diversity and nutritional quality of available food, whilst potentially diminishing pollination service capabilities.Summary StatementAcute neonicotinoid exposure impaired flight endurance and affected velocity ofBombus terrestrisworkers, which may dramatically reduce colony foraging potential and pollination provision in pesticide applied landscapes.

Aiming at the requirements of the weapon system of UAV when it flies over the sea at ultra-low altitude, the research on ultra-low altitude flight dynamics modeling, ultra-low altitude information fusion technology and flight mission profile was carried out for a certain UAV, and the semi-physical simulation and flight verification were carried out. The results show that the improvement and optimization of UAV ultra-low altitude flight control is reasonable and feasible.

Unmanned Aerial Vehicles have widely demonstrated their utility in military applications. Different vehicle types airplanes in particular have been used for surveillance and reconnaissance missions. Civil use of UAVs, as applied to early alert, inspection and aerialimagery systems, among others, is more recent (OSD, 2005). For many of these applications, the most suitable vehicle is the helicopter because it offers a good balance between manoeuvrability and speed, as well as for its hovering capability. A mathematical model of a helicopter’s flight dynamics is critical for the development of controllers that enable autonomous flight. Control strategies are first tested within simulators where an accurate identification process guarantees good performance under real conditions. The model, used as a simulator, may also be an excellent output predictor for cases in which data cannot be collected by the embedded system due to malfunction (e.g. transmission delay or lack of signal). With this technology, more robust fail-safe modes are possible. The state of a helicopter is described by its attitude and position and the characteristics of its dynamics system correspond to those of a non-linear, multivariable, highly coupled and unstable system (Lopez, 1993). The identification process can be performed in different ways, on analytical, empirical or hybrid models, each with its advantages and disadvantages. This Chapter describes how to model the dynamic of a mini-helicopter using different kinds of supervised neural networks, an empirical model. Specifically, the networks are used for the identification of both attitude and position of a radio controlled mini helicopter. Different hybrid supervised neural network architectures, as well as different training strategies, will be discussed and compared on different flight stages. The final aim of the identification process is to build a realistic flight model to be incorporated in a flight simulator. Although several neural network-based controllers for UAVs can be found in the literature, there is little work on flight simulator models. Simulators are valuable tools for in-lab testing and experimenting of different control algorithms and techniques for autonomous flight. A model of a helicopter’s flight dynamics is critical for the development of good a simulator. Moreover, a model may also be used during flight as predictor for anticipating the behaviour of the helicopter in response to control inputs. The Chapter first focuses on two neural-network architectures that are well suited for the particular case of mini-helicopters, and describes two algorithms for the training of such neural-network models. These architectures can be used for both multi-layer and radial-based

This paper presents the technique to implement stability and control of multirotor unmanned aerial vehicle (UAV). The output of the inertial sensors like accelerometer and gyroscope is noisy. These sensors are used to get the orientation and attitude of the UAV. Most of the flight controllers available these days are built to fly in a very specific environment. One cannot fly with these flight controllers in heavy wind or where precise control is required. As a result, the UAV’s that use these flight controllers feel unresponsive and sloppy. The goal here is to get excellent flight dynamics and robust flight control which can fly in any conditions. The UAV’s should be able to do aggressive maneuvering, fault tolerance etc. In the proposed design, Kalman Filter algorithm is implemented to get precise values from Inertial Measurement Unit. Extended Kalman Filter (EKF) is used for sensor fusion and to get precise values from Inertial Measurement Unit PID algorithms are used to stabilize the UAV and for maneuver Rotational speed of the four motors can be increased or decreased independently to correct the orientation or position. The flight controller is built with STM32F4 ARM controller.

High quality simulation environment can accelerate the development of the control software. Also, it is a good tool for the beginner to study how the control software works. The goal of this paper is aiming at designing a real time HIL experimental platform for quadrotor autopilot software design, validation and optimization. The platform is mainly composed of four blocks: A quadrotor dynamics model, a flight control system, a communication agent and hardware devices for control input and output. The flight dynamics model of a quadrotor build in this paper is to simulate the physics involved with its movement. It receives input signals from the autopilot controller, and returns the quadrotor’s real time pose, position, velocities, and etc. resulting from the input signals to the autopilot controller. A communication agent implements bidirectional communication between the flight dynamics model and the autopilot controller. Hardware devices for input and output is used to change the flight mode, indicate the flight state and test the control law. This paper focuses primarily on developing an experiment platform that works for control software validation. It allows for the safe testing of experimental code and settings, especially for aggressive and agile flight test.

The Guidance, Navigation and Control (GNC) of air and space vehicles has been one of the spearheads of research in the aerospace field in recent times. Using Global Navigation Satellite Systems (GNSS) and inertial navigation systems, accuracy may be detached from range. However, these sensor-based GNC systems may cause significant errors in determining attitude and position. These effects can be ameliorated using additional sensors, independent of cumulative errors. The quadrant photodetector semiactive laser is a good candidate for such a purpose. However, GNC systems&rsquo, development and construction costs are high. Reducing costs, while maintaining safety and accuracy standards, is key for development in aerospace engineering. Advanced algorithms for getting such standards while eliminating sensors are cornerstone. The development and application of machine learning techniques to GNC poses an innovative path for reducing complexity and costs. Here, a new nonlinear hybridization algorithm, which is based on neural networks, to estimate the gravity vector is presented. Using a neural network means that once it is trained, the physical-mathematical foundations of flight are not relevant, it is the network that returns dynamics to be fed to the GNC algorithm. The gravity vector, which can be accurately predicted, is used to determine vehicle attitude without calling for gyroscopes. Nonlinear simulations based on real flight dynamics are used to train the neural networks. Then, the approach is tested and simulated together with a GNC system. Monte Carlo analysis is conducted to determine performance when uncertainty arises. Simulation results prove that the performance of the presented approach is robust and precise in a six-degree-of-freedom simulation environment.

Miniaturized atomic clocks with high frequency stability as local oscillators in global navigation satellite system (GNSS) receivers promise to improve real-time kinematic applications. For a number of years, such oscillators are being investigated regarding their overall technical applicability, i.e., transportability, and performance in dynamic environments. The short-term frequency stability of these clocks is usually specified by the manufacturer, being valid for stationary applications. Since the performance of most oscillators is likely degraded in dynamic conditions, various oscillators are tested to find the limits of receiver clock modeling in dynamic cases and consequently derive adequate stochastic models to be used in navigation. We present the performance of three different oscillators (Microsemi MAC SA.35m, Spectratime LCR-900 and Stanford Research Systems SC10) for static and dynamic applications. For the static case, all three oscillators are characterized in terms of their frequency stability at Physikalisch-Technische Bundesanstalt, Germany's national metrology institute. The resulting Allan deviations agree well with the manufacturer's data. Furthermore, a flight experiment was conducted in order to evaluate the performance of the oscillators under dynamic conditions. Here, each oscillator is replacing the internal oscillator of a geodetic-grade GNSS receiver and the stability of the receiver clock biases is determined. The time and frequency offsets of the oscillators are characterized with regard to the flight dynamics recorded by a navigation-grade inertial measurement unit. The results of the experiment show that the frequency stability of each oscillator is degraded by about at least one order of magnitude compared to the static case. Also, the two quartz oscillators show a significant g-sensitivity resulting in frequency shifts of − 1.2 × 10−9 and + 1.5 × 10−9, respectively, while the rubidium clocks are less sensitive, thus enabling receiver clock modeling and strengthening of the navigation performance even in high dynamics., Bundesministerium für Wirtschaft und Energie http://dx.doi.org/10.13039/501100006360, Gottfried Wilhelm Leibniz Universität Hannover (1038)

TZ-1 satellite is the first Software Define Satellite, which is developed by Shanghai Engineering Center for Microsatellites and intends to validate software define technology in orbit. TZ-1 satellite is a typical low-cost satellite and equipped with the attitude control components, including sun sensors, magnetometers, magnetic torquers and a momentum wheel. Based on these low-cost attitude control components, a high-reliable attitude control scheme is proposed and the well-designed algorithms provide a good attitude pointing accuracy and proper stability for the satellite, which make the implements of the relative experiments possible. ADCS (Attitude determine and control system) simulations show that the designed rate damping algorithm for large angular velocity cases could de-tumble the satellite perfectly, even if the initial angular velocity is up to 70 deg/s. The sun pointing algorithm is robust and sun angle is always lower than 20 degrees. The nadir pointing algorithm is perfect and the satellite pointing accuracy and stability have been well guaranteed. According to the telemetry data, attitude control system works well, attitude curve changes are consistent with the simulations, and the satellite pointing accuracy and stability are the same with expectations. Attitude control system of TZ-1 components is a low-cost but robust one, which could be used for reference by the following low-cost LEO satellites.

In order to realize the rapid verification of the control algorithm of the tilt tri-rotor UAV, this paper presents the design and implementation of the SIL(software in the loop) simulation system using X-plane software. Firstly, According to the actual parameters of the designed tilt tri-rotor UAV, a full scale digital model that can simulate actual flight dynamics is designed by Plane Maker. Secondly, the flight control scheme consists of mode transition strategy, hybrid controller and control allocation is illustrated and carried out using Matlab/Simulink. Then, using UDP protocol, the UAV model based on X-Plane and the controller based on MATLAB / Simulink are combined to form the SIL simulation system. Finally, the flight simulations are finished using the SIL system, and the results show that the designed simulation system is suitable for the verification of the flight control algorithm of the tilt tri rotor UAV.

Digital avionic solutions enable advanced flight control systems to be available also on smaller aircraft. One of the safety-critical segments is the air data system. Innovative architectures allow the use of synthetic sensors that can introduce significant technological and safety advances. The application to aerodynamic angles seems the most promising towards certified applications. In this area, the best procedures concerning the design of synthetic sensors are still an open question within the field. An example is given by the MIDAS project funded in the frame of Clean Sky 2. This paper proposes two data-driven methods that allow to improve performance over the entire flight envelope with particular attention to steady state flight conditions. The training set obtained is considerably undersized with consequent reduction of computational costs. These methods are validated with a real case and they will be used as part of the MIDAS life cycle. The first method, called Data-Driven Identification and Generation of Quasi-Steady States (DIGS), is based on the (i) identification of the lift curve of the aircraft, (ii) augmentation of the training set with artificial flight data points. DIGS&rsquo, s main aim is to reduce the issue of unbalanced training set. The second method, called Similar Flight Test Data Pruning (SFDP), deals with data reduction based on the isolation of quasi-unique points. Results give an evidence of the validity of the methods for the MIDAS project that can be easily adopted for generic synthetic sensor design for flight control system applications.

Pose estimation is of paramount importance for flight control as well as localization and navigation of Unmanned Aerial Vehicles (UAVs) to enable autonomous operations. In environments without GPS, such estimation can only be determined using onboard sensors; optical flow using a monocular camera is a popular approach. Monocopters are a class of nature inspired UAVs known as free rotors where their design and flight dynamics are inspired by the falling samara seed. With a constantly rotating body frame, free rotors introduces some unique challenges for visual perception required during optical flow sensing. This paper addresses these problems with the introduction of SHIFT (Selective Heading Image for Translation) that selects optimal images for determining translation with optical flow. It achieves this by decoupling rotation vectors about the optical axis from translation vectors in a flow field through the separate tracking of orientation and position using an Unscented Kalman Filter with phase correlation in the log-polar and spatial domain. The experiments show that SHIFT’s estimation in orientation is stable even under sinusoidal excitation with a median absolute percentage errors of less than 1 %. It is able to track position and orientation of a UAV accurately.

We propose a novel anomaly detection framework for a fleet of hybrid aerial vehicles executing high-speed package pickup and delivery missions. The detection is based on machine learning models of normal flight profiles, trained on millions of flight log measurements of control inputs and sensor readings. We develop a new scalable algorithm for robust regression which can simultaneously fit predictive flight dynamics models while identifying and discarding abnormal flight missions from the training set. The resulting unsupervised estimator has a very high breakdown point and can withstand massive contamination of training data to uncover what normal flight patterns look like, without requiring any form of prior knowledge of aircraft aerodynamics or manual labeling of anomalies upfront. Across many different anomaly types, spanning simple 3sigma statistical thresholds to turbulence and other equipment anomalies, our models achieve high detection rates across the board. Our method consistently outperforms alternative robust detection methods on synthetic benchmark problems. To the best of our knowledge, dynamics modeling of hybrid delivery drones for anomaly detection at the scale of 100 million measurements from 5000 real flight missions in variable flight conditions is unprecedented.

In civil aviation, navigation performance has to be maintained up to a high standard for its uninterrupted operations. Global navigation satellite systems (GNSS) coupled with other navigational aid system provide the required performance levels for flight operations. In GNSS based position estimates, the vertical component is less accurate than the horizontal component; it is specifically due to the necessity of estimating a receiver clock bias. In all phases of flight navigation, the accuracy of height component is extremely important. With the concept of receiver clock modeling (RCM), sometimes also referred as clock coasting, the accuracy of the vertical component can be improved by a large extent. In this paper, we present experimental results of GNSS code-based flight navigation with and without RCM. GNSS observations are captured during a flight for about three hours with multiple geodetic grade GNSS receivers and an inertial measurement unit (IMU). Some of the receivers are connected with external atomic clocks to analyze the feasibility and validity of RCM in flight navigation; also to study the impact of flight dynamics on the external clocks and GNSS observations. Data captured are processed post-flight; position and clock errors are estimated with multi-GNSS code and Doppler observations using a Kalman filter (KF) approach. The estimated position and clock errors are computed twice, once by applying the concept of RCM and once without applying it. Finally, the estimated positions are compared with the reference trajectory and the topocentric coordinate differences are evaluated. Experimental results demonstrate that the precision in the height component is improved by about 65% using GPS and Galileo P-code observations with RCM applied compared to a positioning solution without applying RCM. Overall, there is no significant difference in the horizontal components for the solution computed with and without RCM. The effects of flight dynamics on external atomic clocks and GNSS observations are also discussed briefly. There exists a high correlation (about 90%) between flight acceleration and the frequency offset of an external atomic ovenized quartz oscillator during a highly dynamic maneuver phase.

Star Trackers are often the most accurate instrument in an Attitude Determination and Control Systems, but often present a slow update rate, requiring additional sensor and sensor fusion algorithms to provide a smoother and faster output. However, the available rate gyros are either noisy, or expensive and heavy. The proposed work investigates the feasibility of high-speed star trackers with modern optics, sensors, and computing systems. Firstly, we investigate the sensitivity of an optoelectrical acquisition system stimulated by dim stars, secondly, we propose and evaluate an algorithm designed to operate at high speed and to be compatible with an Field-Programmable Gate Array implementation, before evaluating the performance of the implementation on FPGA. Finally, we debate the usability of such a system, both in terms of compatibility with a mission and CubeSat ecosystems, and in terms of performance. As a result, aside from removing the need for a rate gyro, Attitude Determination and Control Systems overall pointing performances can be increased. The proposed attitude determination system achieved a 0.001&deg, accuracy, with a 99.1% sky coverage and an ability to reject false-positive while performing a single-frame lost-in-space star identification at a 50 Hz update rate with a total delay of 19 ms, including 13 ms.

We are proposing a technology demonstration mission for JPL's Inter-Satellite Optical Communicator (ISOC). The ISOC has the potential to enable up to 1 Gbps data rates over a distance up to 200 km in free space. Key features of the ISOC include full sky coverage and the ability to maintain multiple links simultaneously. The Q4 mission consists of (4) 6U CubeSats furnished with ISOCs to demonstrate high data rate communications among the spacecraft. More specifically, we seek to demonstrate the omnidirectionality of the ISOC by providing simultaneous optical links between one spacecraft and the other three. Q4 will be a demonstrator for small spacecraft swarm capabilities. Following a proposed deployment from the ISS, the CubeSats will utilize their onboard thrusters to enter their desired orbit. The orbit consists of one “leader” spacecraft in a circular orbit with a 400 km LEO altitude and three “follower” spacecraft in slightly elliptical orbits rotating azimuthally about the leader. The main mission will consist of three consecutive phases: First, the spacecraft will demonstrate pointing, acquisition, and tracking using newly developed protocols. Next, link establishment and different channel access methods (CDMA and TDMA) will be tested. Finally, Delay Tolerant Network protocols will be implemented to allow fast data sharing among the spacecraft. The distance between the communicating spacecraft will be increased as the mission progresses to characterize the link quality as a function of distance. All communications over the course of the mission will be recorded and analyzed on the ground using bit error rate as a metric for success. The current design for each the four Q4 CubeSats contains an XACT advanced ADCS system for precision beam pointing. Other components currently under consideration include MiPS cold gas thrusters for orbital maneuvering and gimbaled eHaWK 84W solar arrays. In this paper we present design considerations for the Q4 CubeSats, link budget calculations, results from preliminary mission analysis, and expected results.

CloudSat, now in its 13th year on orbit, has employed various strategies over its lifetime to compensate for a weakened battery and the loss of a reaction wheel. The creative efforts required to keep the mission going have been documented in a number of earlier papers [1]–[4]. This paper focuses on a prospective change in on-orbit operations which will help maintain or reduce the current loads on the battery in eclipse and enhance mission longevity. Keeping the battery healthy drives many of the operational modes on the SC (spacecraft) and seasonal operational adjustments have often been required in the past. In the normal mode of operation, called DO-Op (Daylight only Operations), science data is collected only during the daylight portion of the orbit and then the spacecraft goes into a spin stabilized, low power, hibernate mode in eclipse. To implement DO-Op, the spacecraft exits umbra spinning with the +X axis pointed at the sun. Then, after capturing attitude control, the spacecraft performs an approximately 180 deg yaw around the boresight of the CPR (Cloud Profiling Radar) so that at umbra entry the +X axis is again pointed at the sun. The spin rate in eclipse is high enough to maintain the orientation of the +X axis but low enough and properly timed to simplify capture at umbra exit. The largest load in umbra is the thermostatically controlled CPR Stability Heater. As the vehicle has aged, there has been a yearly trend towards increased CPR stability heater on-time which has reduced already critical power margin. The on-time of the CPR stability heater varies during the year and in the summer season the heater, which is not manually controllable, turns on longer resulting in the minimum power margin. The concern was that, if this trend continued, coupled with loss of capacity as the battery ages, it would be necessary to suspend science data collection for longer and longer periods in the summer. Reducing loads in eclipse would, of course, maintain the science collection and ultimately increase the mission's lifetime. A new operational mode called Hip-Hop (Hi Power Amplifier Heater Operation) has been developed which accomplishes this goal. In Hip-Hop a carefully timed sequence of SC attitudes exposes the CPR -X radiator to the Sun while simultaneously maintaining uninterrupted science operation. On-orbit tests have confirmed that this mode significantly reduces the heater on time. This paper will discuss the design of Hip-Hop, illustrating the ADCS impacts, and the predicted thermal and power usage improvements. Detailed software test bench runs will be discussed, as will results from on-orbit testing.

High-resolution orbital imagery from the LROC reveals evidence of subsurface voids and mare-pits on the lunar surface. Similar discoveries have been made with the HiRISE camera onboard the MRO observing the Martian surface. These accessible voids could be used for a future human base because they offer a natural radiation and micrometeorite shield and offer constant habitable temperatures. Exploration of these extreme and rugged environments remains out of reach from current planetary rovers and landers. A credible solution is to develop an architecture that permits taking high exploratory risks that translates into high reward science. Rapid advancement in electronics, sensors, actuators, and power have resulted in ever-shrinking devices and instruments that can be housed in small platforms. We propose to use a small, low-cost, modular spherical robot called SphereX that is designed to hop and roll short distances. Each robot is of several kilograms in mass and several liters in volume. Each SphereX will consist of space-qualified electronics like command & data handling board, power board for power management and s-band radio transceiver for communication. Power is provided using lithium-ion primary batteries or a PEM fuel cell power supply. Communication is established through multi-hop communication link to relay data from inside the caves to a lander outside on the planetary surface. Since the temperature inside underground lunar pits is expected at -25°C, thermal management for the space-grade electronics is minimal as they can operate up to -40°C, however thermal management for the battery pack and the propellants will be done through active and passive elements. Moreover, SphereX requires use of a propulsion system and Attitude Determination and Control System (ADCS) to perform controlled ballistic hops. Hopping on very-low gravity environments is more time-efficient than rolling due to the reduced traction. In this paper, we present detailed analysis of each subsystem of SphereX and also detailed dynamics and control simulations of SphereX for ballistic hopping and rolling mobility. For ballistic hopping control, the robot has two modes: soft landing mode for traversing long distances and entering the pit through its collapsed entrance, and a fuel-efficient hard landing mode for traversing short distances. We will then present experimental results for mapping unknown cave-like environments which is done using a quadcopter for simulating low-gravity (e.g. Moon, Mars) environments and testing the control algorithms. The quadcopter mimics the dynamics of SphereX and also carries a 3D LiDAR for mapping and navigation. 3D point cloud data collected by the LiDAR is used for performing SLAM and path planning in unknown and GPS-denied environments much like the pits, caves and lava tubes on the Moon and Mars.

Flight investigations of aerodynamics and flight dynamics for a small unmanned aerial vehicle (UAV) demand the usage of automatic data acquisition system to support valid estimation of UAV aerodynamics and flight performance. All subsystems consist of commercial hardware component and popular component in the market. The system is low weight, low power, small in dimension, and low cost. The feature of this FDAU is nine degrees of freedom (9-DOF) inertial measurement unit (IMU) with 3-axis accelerometer, 3-axis gyroscope, and 3-axis magnetometer, global navigation satellite system (GNSS) and storage device. FDAU combines a large variety of sensor streams into a unified state data stream that is recorded for later aerodynamic analysis. This FDAU works by taking data from IMU sensor and GNSS, converts the signal to the correct level and filters the signal analog using signal conditioning, and then the data is switch-selected, connecting one channel at a time by multiplexer. The data is converted using converter (analog to digital or digital to analog signal), before it is processed by central processing unit (CPU) to generate become values who indicated a many flight parameter also to process with Kalman Filter, and then data is recorded by storage device. The results of this research show that the initial design of FDAU can record 13 different flight parameters. Not only that by using Kalman Filter concept, but the quality of resulting data is also better than the raw sensor data, from there the data has been successfully stored in the storage device with spreadsheet format.

In the paper, the problem of minimum-fuel aeroassisted spacecraft regional reconnaissance (orbital hopping) is considered. A new nonlinear constrained optimal control formulation is designed and constructed so as to describe this mission scenario. This formulation contains multiple exo-atmospheric and atmospheric flight phases and correspondingly, two sets of flight dynamics. The constructed continuous-time optimal control system is then discretized via a multi-phase global collocation technique. The resulting discrete-time system is optimized using a newly proposed gradient-based optimization algorithm. Several comparative simulations are carried out and the obtained optimal results indicate that it is effective and feasible to use the proposed multi-phase optimal control design for achieving the aeroassisted vehicle orbital hopping mission.

Korea’s first lunar mission, the Korea Pathfinder Lunar Orbiter (KPLO), aims to launch in mid-2022 via the Space-X Falcon-9 launch vehicle. For the successful flight operation of KPLO, the Korea Aerospace Research Institute (KARI) has designed and developed the Flight Dynamics Subsystem (FDS). FDS is one of the subsystems in the KPLO Deep-Space Ground System (KDGS), which is responsible for the overall flight dynamics-related operation. FDS is currently successfully implemented and meets all of the requirements derived from the critical design phases. The current work addresses the design and implementation results for the KPLO FDS. Starting from overviews on KPLO payloads, bus systems, and mission trajectory characteristics, a review on KDGS is also treated briefly. Details on the design philosophy, unique characteristics, and functionalities of all six different modules nested inside the FDS with its Graphical User Interface (GUI) design are discussed. Moreover, efforts currently devoted to the flight operation preparation of the KPLO are summarized, including many collaborative works between KARI and the National Aeronautics and Space Administration (NASA) teams.

Attitude Determination and Control Subsystem (ADCS) in spacecraft is one of the vital systems for low-earth-orbit spacecraft in which the pointing accuracy is a highly recommended factor to satisfy its mission requirements. When any malfunction takes place at attitude actuator, the spacecraft will not satisfy the required mission objectives. It is required to identify specific faults for attitude actuators in a manner that helps to optimally recover this type of anomaly. An efficient anomaly detection and identification technique is a suitable way to identify such anomaly. This research introduces an accurate and high-performance methodology for fault detection and identification for spacecraft reaction wheels (RW) as (ADCS) actuator. Proposed approach is to differentiate among signatures of possible anomalies that may be occurred at RW like under-voltage, over-voltage, current losses, temperature decrease, and temperature increase. “Prony method,” as a feature extraction technique, is used to discriminate between normal system behavior and anomalies based on the three-axis spacecraft RW operation. A feed-forward neural network with back-propagation algorithm is used for anomaly identification. Prony order assessment is also carried out to obtain the proper order of poles and zeros to minimize the processing time required for identification. The results verify that the proposed anomaly identification is successfully accomplished with high degree of confidence and with minimal execution time. Research approach leads to generic methodology for anomaly identification process among all spacecraft subsystem anomalies.

During the spacecraft (SC) mission, some of orbital elements change during the flight, the need to study the spacecraft maneuvers become paramount importance need. A full mathematical model for the Spacecraft lifetime maneuvers is deduced, implemented in a simulation scenario with a GUI, and then desired simulation is verified during the different operations' phases such as orbit transfer, propagation, maintenance and deorbiting. In the current article, an interpretation of the carried-out model will be introduced to match a real case of mission analysis as possible for newly designed satellite. Two types of orbits (inclined and Sun synchronous Orbit SSO) are investigated for the SC mission analysis over the whole lifetime phases. The investigation is carried out using two types of power systems (electrical and chemical) using the same propellant tank model with capacity 60 kg. A numerical comparison was concluded for both studied power systems.

Satellite missions rely on orbital dynamics calculations at every step, from initial mission analysis at conceptual design phase to disposal at the end of mission. Therefore, the accuracy, fidelity, versatility and reliability of this tool can be deemed to be a key contributor to mission success. This paper presents the current status, selected functionalities and performance of the Orbital Dynamics System software developed in-house for TUBITAK UZAY to meet the mission analysis to operational flight dynamics computation needs. The software is written purely in Java and features state-of-the-art multi-threading and service-based-architecture, in addition to precise orbital mechanics analysis, modelling, estimation and control functionalities. This software has been used in an operational setting for RASAT and GOKTURK-2 satellites for a combined duration of more than 14 years.

The Cyclone Global Navigation Satellite System constellation of eight micro-satellites in low-Earth orbit was designed to provide continuous, gap-free coverage for hurricane forecasting and monitoring throughout the life-cycle of a tropical storm. To provide the capability, the spacecraft Attitude Determination and Control System must accurately and reliably slew and hold its attitude - and by extension, its payload data collection antennae - to prescribed knowledge and pointing requirements. The CYGNSS constellation launched in December 2016 and has been collecting and serving data since the start of the tropical storm period in 2017. This paper presents the flight performance of the ADCS system in key ADCS modes and compares its on-orbit performance to its design and simulation predicted responses. Flight telemetry analysis uncovered an anomaly in one of the ADCS modes that interfered with the spacecraft's observatory mode and induced a sustained, once-per-orbit pitch oscillation in all eight spacecraft. This anomaly was conjectured to trace to a spurious magnetic dipole induced on the spacecraft due to some electrical effects in the main power circuitry. This root-cause analysis is summarised in this paper as is the retuning that was undertaken on the estimation and control system parameters to improve disturbance prediction and rejection within the existing ADCS architecture. Data is presented from spacecraft simulations as well as flight, before and after the redesign, that shows the efficacy of the redesigned ADCS system to reject the spurious, anomalous disturbance and recover the required performance.

Utilization of satellites to meet the needs of various missions requires a reliable Attitude Determination and Control System (ADCS). In this paper, we presents a robust design of the ADCS for the ESTCube-2 nanosatellite. The primary aim of the ADCS is to provide angular momentum to deploy a 300-meter tether used in a plasma brake deorbiting experiment. This is achieved by spinning up the three-unit CubeSat to 360 degrees per second about the short axis, deploying the tether and repeating the spin-up-deployment sequence until the whole tether is deployed. The system also provides accurate pointing for an Earth observation camera and a high-speed communication system. In addition to basic sensors and actuators commonly used on nanosatellites, the design includes a cold-gas propulsion system and a star tracker which will be tested for the future use in deep space. In order to operate the Earth observation and high-speed communication payloads, the satellite will use reaction wheels and the star tracker to achieve pointing the accuracy better than 0.25 degrees and the stability better than 0.125 degrees per second. To achieve the control requirements, a Lyapunov-based stability function and an optimal linear-quadratic regulator control is implemented. The attitude determination is handled by an unscented Kalman filter, which is deployed on a Cortex-M7 microcontroller. The ESTCube-2‘s plasma brake experiment in low Earth orbit serves as a precursor of ESTCube-3 which will test similar technology - the electric solar wind sail - for interplanetary propulsion in lunar orbit.

This paper presents the Flight Instruments and Flight Visualization Libraries developed within the DLR Institute of System Dynamics and Control. For the design of dynamic models and control systems, a visual evaluation of the dynamic simulation is indispensable for a successful design and test process. Especially when it comes to aircraft models, an overview of the overall dynamics is needed. Therefore, the presented libraries provide fast assembly of fully configurable and generic flight visualization tools in which the view positions as well as the setup of Primary Flight Displays can be chosen freely. This provides the visual components of a rapid prototyping environment which can be used in the development of flight dynamic models and flight control laws. Moreover, the camera views and displays can easily be reconfigured for each purpose and research focus area. Furthermore, the libraries can be used for desktop simulation, motion simulator experiments as well as flight testing on a real aircraft.

A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sample data to train models. In addition to the hovering state, the signal samples of small unmanned aerial vehicles (UAVs) should also include flight dynamics, such as vertical, pitch, forward and backward, roll, lateral, and yaw. However, it is difficult to collect all dynamic UAV signal samples under actual flight conditions, and these dynamic flight characteristics will lead to the deviation of the original features, thus affecting the performance of the recognizer. In this paper, we propose a small UAV m-DS recognition algorithm based on dynamic feature enhancement. We extract the combined principal component analysis and discrete wavelet transform (PCA-DWT) time–frequency characteristics and texture features of the UAV’s micro-Doppler signal and use a dynamic attribute-guided augmentation (DAGA) algorithm to expand the feature domain for model training to achieve an adaptive, accurate, and efficient multiclass recognition model in complex environments. After the training model is stable, the average recognition accuracy rate can reach 98% during dynamic flight.

A combination of vibrational inputs and state feedback is applied to control the flight of a biomimetic air vehicle. First, a control strategy is developed for longitudinal flight, using a quasi-steady aerodynamic model and neglecting wing inertial effects. Vertical and forward motion is controlled by modulating the wings’ stroke and feather angles, respectively. Stabilizing control parameter values are determined using the time-averaged dynamic model. Simulations of a system resembling a hawkmoth show that the proposed controller can overcome modeling error associated with the wing inertia and small parameter uncertainties when following a prescribed trajectory. After introducing the approach through an application to longitudinal flight, the control strategy is extended to address flight in three-dimensional space.

This paper discusses active laser control using a genetic algorithm and a mirror-actuating system to achieve kilometer-order in-air flight using a laser propulsion vehicle while riding a beam. A 10 kg vehicle reaction driven by a strong shock wave is examined using our flight simulator to analyze interaction with unsteady blast wave propagation based on coupling calculation between hydrodynamic simulation of the shock wave propagation and orbital simulation of the vehicle flight motion, and the generated impulses are characterized by the spherically symmetric Sedov solution. Beam-riding flight with an initial y offset of 5 mm is successfully sustained by controlling angular offset, while vehicle acceleration is kept low for safe launch to the target altitude. A system delay of laser control is introduced into the flight simulator, and beam-riding flight is maintained for a 20 ms system delay using delay correction following prediction by six-degree-of-freedom equations of motion. This study also examines ...

Micro Vehicles (MAVs) are small sized Unmanned Aerial Vehicles with applications in the fields of surveillance, Disaster management, remote sensing, Environmental monitoring etc. In this project, we are interfacing Pressure sensor and 9-DOF MPU sensor for estimation of flight parameters such as pressure, temperature and altitude from pressure sensor. Using MPU sensor we can estimate the accelerometer and gyroscope values to control direction of MAV. The ARM Cortex -M4 processor based Discovery board uses Inter Integrated Circuit (I2C) and communication protocol to extract the raw values of these varying parameters from the sensors. The raw values of each sensor are processed individually to obtain the calibrated parameters. The critical flight dynamics parameters, Roll, Pitch and Yaw, are calculated using the obtained calibrated values. These continuous real-time values obtained from the sensors are estimated.

The article presents the development of a simulation mathematical model’s algorithm to evaluate radars resolution capability. The targets inputs and their feasible changes in the flight dynamics of multiple target have been examined. The mechanism for the analysis of multiple target composition has been demonstrated.

The simulation system for Multi-UAV cooperative target tracking is an important supporting tool, needed by theoretical verification, algorithm experiment and 3D real-time visual simulation. Firstly, based on the HLA standard, the 3D simulation system is designed through functional orientation, structure design and operation process management. Then on the basis of flight dynamics of UAV, Aerosim Toolbox is used for simulation system. Meanwhile a method of realtime and seamless rendering of infinite terrain is implemented by block duplication, and the management of the detail scene is realized with BSP method. Thus the key technology of the simulation system is built. If users understand the relevant interface protocol, they can design their own algorithms and do experiments on the simulation platform. Finally, the platform is used to simulate the formation control algorithm and Multi-UAV target tracking flight control algorithm. The simulation results show that the system has strong generality and fidelity.

The offline development, validation and verification of the software for an airborne strapdown inertial navigation system (SINS) requires that the simulation of the inertial measurement unit (IMU) be based on representative flight dynamics data. This paper presents our efforts to combine an existing, popular and open-source flight dynamics model (FDM) with an IMU simulator we developed for the purpose of such work. We will show how it is possible to use the FDM and IMU simulator to develop, evaluate and improve SINS software. This development also allows for validation and verification of the end software product.

This paper presents methodology to determine dynamic models and the suitable controllers for FY450 Firefly quadcopter. Frequency response system identification technique via software package Comprehensive Identification from Frequency Response (CIFER) was applied in this research. Pixhawk hardware with PX4 Flight stack firmware was implemented as a flight controller. The measurement of inputs and outputs during hovering flight maneuver with frequency sweep input was utilized to determine the unknown parameters of SISO mathematical model. Then after mathematical models were identified, the dynamic models of roll, pitch and yaw response respectively were employed to tuning the gains of PX4 controller structure with globally offline optimization technique. With this presented method, satisfied flight dynamics meets the desired performances without the requirement of numerous in-flight tuning.

Distributed Space Systems (DSS) promise advances in space science, earth and planetary science, as well as on-orbit servicing and space situational awareness. In order to mimic a large spacecraft with gigantic and reconfigurable aperture, DSS rely on precise knowledge of the relative position/velocity of the co-orbiting satellites. Especially in Earth’s orbit, Global Navigation Satellite Systems (GNSS) can provide centimeter-level or better relative navigation solutions through differential carrier-phase processing techniques on cooperative satellites. The development of these GNSS functionalities and the verification of their capability to meet next-generation space mission requirements necessitate a high-fidelity testing environment. This research presents the design, development, and verification of the Stanford GNSS navigation testbed for spacecraft formation-flying and rendezvous. Key aspects of the system architecture are illustrated, including the orbital dynamics simulation, the GNSS signal and measurement generation, and the algorithms/software for advanced navigation applications. Each subsystem of the testbed is thoroughly verified through comparisons with flight data from space missions, live signals from static scenarios, and realistic hardware-in-the-loop simulations. Specifically, orbit propagation results are compared against precise flight dynamics products from the PRISMA formation-flying mission. A cross-verification method is introduced to validate the GNSS signal simulator and a software receiver emulator using a live signal source. In particular, an Extended Kalman Filter is used to quantify the distribution of pseudorange and carrier-phase measurement residuals from each signal source. The measurement residual statistics, along with satellite tracking performance, are then used as comparison metrics to verify that all stimulation methods are consistent with one another. After verification of the testbed, a commercial-off-the-shelf GNSS receiver is characterized using a zero-baseline test in order to quantify the measurement noise and assess its capability to support precision navigation on nanosatellites. Finally, the testbed is used to assess the performance of the Distributed multi-GNSS Timing and Localization system (DiGiTaL), a precision navigation payload for small satellite swarms under development at Stanford in collaboration with NASA Goddard Space Flight Center.

Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

This paper presents a method for the development of artificial neural networks (ANN) that consists in the use of a search space algorithm to adjust the components of an ANN’s initial structure, based on the performance obtained by different network configurations. Also, it is possible to represent an ANN’s structure as a genetic sequence, which enables directly loading a corresponding genetic sequence to instantly generate and run a previously trained ANN. This paper also shows some results obtained by different ANNs developed by this method, which demonstrate its features by analyzing its accuracy and trueness. As an example for application of this method, a case study is presented for a specific flight simulation, using data obtained from a helicopter’s flight dynamics simulator for ANN training. Helicopter flight dynamics is a relevant study, for it can be used, for example, to provide precise data to a flight simulator, which implies in an important issue for pilot training, and subsequently, this type of application may help reducing the probability of pilot’s faults in a real flight mission. Finally, some considerations are made about the work shown in this paper as the results, discussions and conclusions are presented.

In this paper, an application for the control system design of JSBSim autopilot is described and its function is demonstrated. The program facilitates the whole process, from creation, through adjustment, to simulation. The results show that the application and the used method are sufficiently functional. The first section introduces the autopilot and script definition in JSBSim flight dynamics model (FDM). The main section shows the control system designer and an example, conditions and results of a simulation process.

In recent years, unmanned aerial vehicles with electric propulsion have taken a substantial UAV market share. Electric driving power provides a clean and simple operation, reliability and ease of maintenance. Electric power plants also have low levels of noise and vibration. The purpose of this article is to provide an algorithm for selection of UAV’s electric propulsion parameters for the route, consisting of different flight modes. Small class UAV which performs the flight on the route with areas of climb, level flight and turn has been analyzed. This article describes mathematical models suitable for numerical calculation: the aerodynamic characteristics of UAV, the elements of UAV’s electric propulsion system, flight dynamics in different flight modes. Further, these mathematical models were linked in one algorithm. According to the algorithm the software for the calculation has been created. For different flight routes the configuration of the electrical power plant with high efficiency on the route has been calculated. The effects of the battery current and voltage settings on the propulsion efficiency have been investigated. Calculations results according to the algorithm showed that accounting for the flight route allows selecting the parameters of the electrical propulsion system of the UAV, more rational in terms of energy use compared to selection based on one main flight mode.

A closed-loop fault detection problem is investigated for the full-envelope flight vehicle with measurement delays, where the flight dynamics are modeled as a switched system with delayed feedback signals. The mode-dependent observer-based fault detection filters and state estimation feedback controllers are derived by considering the delays’ impact on the control system and fault detection system simultaneously. Then, considering updating lags of the controllers/filters’ switching signals which are introduced by the delayed measurement of altitude and Mach number, an asynchronous H ∞ analysis method is proposed and the system model is further augmented to be an asynchronously switched time-delay system. Also, the global stability and desired performance of the augmented system are guaranteed by combining the switched delay-dependent Lyapunov–Krasovskii functional method with the average dwell time method (ADT), and the delay-dependent existing conditions for the controllers and fault detection filters are obtained in the form of the linear matrix inequalities (LMIs). Finally, numerical example based on the hypersonic vehicles and highly maneuverable technology (HiMAT) vehicle is given to demonstrate the merits of the proposed method.

The problem of the unmanned flight vehicle moving along the given route in a perturbed environment comes down to that of pursuing a target which simulates motion of the reference flight vehicle in compliance with its task. A scheme was proposed of a control system selecting the control strategy according to the current states of the flight vehicle and target. Consideration was given to the issues of the lead determination of the point of meeting of the flight vehicle with the target and rearrangement in the transfer functions of the equations of longitudinal and lateral motions of the flight vehicle in a restless tmosphere. The systems of automatic stabilization of the pitch and yaw angles with autopilot are used as the internal control loops. In the experimental part of the paper, the FV motion is modeled under the control constraints.

Wind tunnel based Virtual Flight Testing (VFT) is a dynamic wind tunnel test for evaluating flight control systems (FCS) proposed in recent decades. It integrates aerodynamics, flight dynamics, and FCS as a whole and is a more realistic and reliable method for FCS evaluation than traditional ground evaluation methods, such as Hardware-in-the-Loop Simulation (HILS). With FCS evaluated by VFT before flight test, the risk of flight test will be further reduced. In this paper, the background, progress, and prospects of VFT are systematically summarized. Specifically, the differences among VFT, traditional dynamic wind tunnel methods, and traditional FCS evaluation methods are introduced in order to address the advantages of evaluating FCS with VFT. Secondly, the progress of VFT is reviewed in detail. Then, the test system and key technologies of VFT for FCS evaluation are analyzed. Lastly, the prospects of VFT for evaluating FCS are described.

The problem of Wing-in-Ground effect affective use in WIG-craft flight by minimization of the average geometrical altitude of flight above sea waves is analysed in the paper. Two concepts of vehicle motion in longitudinal plane are compared. It is shown that the best control law lies between rigid stabilization of average altitude and full freedom in action the self-stabilisation property of WIG-craft. It is proved that only large WIG-craft could provide the essential fuel saving in controlled flying close to the disturbed surface. For small WIG-craft fuel saving against the plane mode of flight is not essential. The modern means of automatic control permit to realize any perfect dynamic features of piloted or autonomous vehicle, and it is important to select the best concept of flight control before developing the control laws for the certain vehicle.

Cluster flight is defined as the operation of multiple cooperative satellites under minimum and maximum distance constraints. Unlike traditional orbit injection of multiple noncooperative satellites, judicious constraints should be imposed on the orbit injection of a cluster. Moreover, the orbital injection should enable a fuel-efficient cluster establishment maneuver. This study develops constraints for the orbit injection of a satellite cluster. Evaluation of feasible orbit injection scenarios is performed. Particular launch vehicles and a concomitant set of orbital injection scenarios are found, which are the most suitable for long-term operation of a cluster. In addition, an efficient cluster establishment control method is developed, which prevents the cluster from drifting apart too rapidly. Several orbit injection scenarios are simulated and their feasibility for a planned cluster flight mission is evaluated. It is shown that both the Polar Satellite Launch Vehicle and the Dnepr launcher can be use...