John Valasek

Vision-Based Sensor and Navigation System for Autonomous Air Refueling

Autonomous in-flight aerial refueling is an important capability for the future deployment of unmanned aerial vehicles, because they will likely be ferried in flight to overseas theaters of operation instead of being shipped unassembled in containers. A reliable sensor, capable of providing accurate relative position measurements of sufficient bandwidth, is key to such a capability. A vision-based sensor and navigation system is introduced that enables precise and reliable probe-and-drogue autonomous aerial refueling for non-micro-sized unmanned aerial vehicles. A performance robust controller is developed and integrated with the sensor system, and feasibility of the total system is demonstrated by simulated docking maneuvers with both a stationary drogue and a drogue subjected to light turbulence. An unmanned air vehicle model is used for controller design and simulation. Results indicate that the integrated sensor and controller enables precise aerial refueling, including consideration of realistic measurement errors and disturbances.

Trajectory Tracking Controller for Vision-Based Probe and Drogue Autonomous Aerial Refueling

This paper addresses autonomous aerial refueling between an unmanned tanker aircraft and an unmanned receiver aircraft using the probe-and-drogue method. An important consideration is the ability to achieve successful docking in the presence of exogenous inputs such as atmospheric turbulence. Practical probe and drogue autonomous aerial refueling requires a reliable sensor capable of providing accurate relative position measurements of su‐cient bandwidth, integrated with a robust relative navigation and control algorithm. This paper develops a Reference Observer Based Tracking Controller that does not require a model of the drogue or presumed knowledge of its position, and integrates it with an existing vision based relative navigation sensor. A trajectory generation module is used to translate the relative drogue position measured by the sensor into a smooth reference trajectory, and an output injection observer is used to estimate the states to be tracked by the receiver aircraft. Accurate tracking is provided by a state feedback controller with good disturbance rejection properties. A frequency domain stability analysis for the combined reference observer and controller shows that the system is robust to sensor noise, atmospheric turbulence, and high frequency unmodeled dynamics. Feasibility and performance of the total system is demonstrated by simulated docking maneuvers of an unmanned receiver aircraft docking with the non-stationary drogue of an unmanned tanker, in the presence of atmospheric turbulence. Performance characteristics of the vision based relative navigation sensor are also investigated, and the total system is compared to an earlier version. Results presented in the paper indicate that the integrated sensor and controller enable precise aerial refueling, including consideration of realistic measurements errors, plant modeling errors, and disturbances.

Evaluation of Longitudinal Desired Dynamics for Dynamic-Inversion Controlled Generic Reentry Vehicles

Dynamic inversion is a control synthesis technique in which the inherent dynamics of a dynamical system are canceledoutandreplacedbydesireddynamics,selectedbythedesigner.Theoutputofsuchaninner-loopcontroller isthecontrol input, whichproducesthedesiredclosed-loop response.Thedesireddynamicsessentially form aloopshaping compensator that affects the closed-loop response of the entire system. This paper attempts to quantify the effect of different forms of desired dynamics on the closed-loop performance and robustness of a dynamicinversion e ight controllerfor reentry vehicles. Proportional, proportional-integral, e ying-quality, and ride-quality forms of desired dynamics are evaluated using time-domain specie cations, robustness requirements on singular values, quadratic cost, and a passenger ride comfort index. Longitudinal controllers are synthesized for a generic X-38 type crew return vehicle, using a set of linear models at subsonic, transonic, and hypersonic e ight conditions. For the candidate forms of desired dynamics and inversion controller structures evaluated here, results indicate that the form used impacts closed-loop performance and robustness and more so for some inversion controller structures more than others. The ride-quality dynamics used with a two-loop angle-of-attack inversion controller provide the best overall system performance, in terms of both time-domain and frequency-domain specie cations, and the evaluation criteria.

Morphing Aerospace Vehicles and Structures

Numerical Techniques Fundamentals of Tactical Missile Guidance Method of Adjoints and the Homing Loop Noise Analysis Covariance Analysis and the Homing Loop Proportional Navigation and Miss Distance Digital Fading Memory Noise Filters in the Homing Loop Advanced Guidance Laws Kalman Filters and The Homing Loop Tactical Zones Strategic Considerations Boosters Lambert Guidance Strategic Intercepts Miscellaneous Topics Ballistic Target Properties Extended Kalman Filtering and Ballistic Coefficient Estimation Multiple Targets Weaving Targets Representing Missile Airframe with Transfer Functions Introduction to Flight Control Design Three-Loop Autopilot Trajectory Shaping Guidance Filtering and Weaving Targets Alternative Approaches to Guidance Law Development Filter Bank Approach to Weaving Target Problem Engagement Simulations in Three Dimensions Advanced Adjoint Applications Miscellaneous Tactical Missile Guidance Topics Comparison of Differential Game Guidance with Optimal Guidance Kinematics of Intercepting a Ballistic Target Boost-Phase Filtering Options Kill Vehicle Guidance and Control Sizing for Boost-Phase Intercept Appendix: Additional Examples Index Supporting Materials

Robust dynamic inversion controller design and analysis for the X-38

vehicle are assumed to be incapacitated, the X-38 flight controller must guide the vehicle autonomously from low earth orbit until deployment of a parafoil during the last minutes of flight. Since the flight envelope of this vehicle extends from hypersonic conditions down to the subsonic regime, its flight controller must deal with large changes in flight conditions. Currently, a Dynamic Inversion (DI) based controller is a prime candidate for the X-38. This controller intends to minimize gain scheduling, but seems to demand a large amount of development time and effort. Abstract A new way to approach robust Dynamic Inversion controller synthesis is addressed in this paper. A Linear Quadratic Gaussian outer-loop controller improves the robustness of a Dynamic Inversion inner-loop controller in the presence of uncertainties. Desired dynamics are given by the dynamic compensator, which shapes the loop. The selected dynamics are based on both performance and stability robustness requirements. These requirements are straightforwardly formulated as frequency-dependent singular value bounds during synthesis of the controller. Performance and robustness of the designed controller is tested using a worst case time domain quadratic index, which is a simple but effective way to measure robustness due to parameter variation. Using this approach, a lateral-directional controller for the X-38 vehicle is designed and its robustness to parameter variations and disturbances is analyzed. The controller analysis is extended to the nonlinear system where both control input displacements and rates are bounded. Overall, this combination of controller synthesis and robustness criteria compares well with the µ-synthesis technique. It also is readily accessible to the practicing engineer, in terms of understanding and use. DI control methodology has gained popularity among control engineers in recent years and has been applied to different types of aircraft applications, such as F-16 1 , F-18 HARV 2 , F-117 3 , Su-27 4 and VSTOL aircraft 5 in addition to applications to missiles 6,7. DI is a controller synthesis technique by which existing deficient or undesirable dynamics are canceled and replaced by designer-specified desirable dynamics. This cancellation and replacement is accomplished by careful algebraic selection of a feedback function. It is for this reason that the DI methodology is also called feedback linearization. The block diagram representation of DI control concept is illustrated in Fig. 1 where CV represents a user-defined control variable. Introduction The X-38, prototype vehicle for the Crew Return Vehicle (CRV), is under development at NASAs Johnson Space …

Unmanned Aerial Vehicles for High-Throughput Phenotyping and Agronomic Research

Advances in automation and data science have led agriculturists to seek real-time, high-quality, high-volume crop data to accelerate crop improvement through breeding and to optimize agronomic practices. Breeders have recently gained massive data-collection capability in genome sequencing of plants. Faster phenotypic trait data collection and analysis relative to genetic data leads to faster and better selections in crop improvement. Furthermore, faster and higher-resolution crop data collection leads to greater capability for scientists and growers to improve precision-agriculture practices on increasingly larger farms; e.g., site-specific application of water and nutrients. Unmanned aerial vehicles (UAVs) have recently gained traction as agricultural data collection systems. Using UAVs for agricultural remote sensing is an innovative technology that differs from traditional remote sensing in more ways than strictly higher-resolution images; it provides many new and unique possibilities, as well as new and unique challenges. Herein we report on processes and lessons learned from year 1—the summer 2015 and winter 2016 growing seasons–of a large multidisciplinary project evaluating UAV images across a range of breeding and agronomic research trials on a large research farm. Included are team and project planning, UAV and sensor selection and integration, and data collection and analysis workflow. The study involved many crops and both breeding plots and agronomic fields. The project’s goal was to develop methods for UAVs to collect high-quality, high-volume crop data with fast turnaround time to field scientists. The project included five teams: Administration, Flight Operations, Sensors, Data Management, and Field Research. Four case studies involving multiple crops in breeding and agronomic applications add practical descriptive detail. Lessons learned include critical information on sensors, air vehicles, and configuration parameters for both. As the first and most comprehensive project of its kind to date, these lessons are particularly salient to researchers embarking on agricultural research with UAVs.

Improved Adaptive–Reinforcement Learning Control for Morphing Unmanned Air Vehicles

This paper presents an improved adaptive-reinforcement learning control methodology for the problem of unmanned air vehicle morphing control. The reinforcement learning morphing control function that learns the optimal shape change policy is integrated with an adaptive dynamic inversion control trajectory tracking function. An episodic unsupervised learning simulation using the Q-learning method is developed to replace an earlier and less accurate actor-critic algorithm. Sequential function approximation, a Galerkin-based scattered data approximation scheme, replaces a K-nearest neighbors (KNN) method and is used to generalize the learning from previously experienced quantized states and actions to the continuous state-action space, all of which may not have been experienced before. The improved method showed smaller errors and improved learning of the optimal shape compared to the KNN.

Observer/Kalman Filter Identification for Online System Identification of Aircraft

The observer/Kalman e lter identie cation method is applied to the problem of online system identie cation of accurate,locallylinear,aircraftdynamicmodelsofnonlinearaircraft.Itisa time-domaintechniquethatidentie esa discreteinput ‐outputmapping from known inputand outputdata samples,withoutuserimposed a prioriassumptions about model structure or model order. The basic formulation of observer/Kalman e lter identie cation specie c to theaircraftproblem isdeveloped and implementedina nonlinear,six-degree-of-freedom simulation of an AV-8B Harrier. A similar simulation of a generic uninhabited combat aerial vehicle is also used. Numerical examples are presented, consisting of longitudinal and lateral/directional successive online identie cations at different nonperfect trim conditions, identie cation with sensor noise on multiple channels, and identie cation with discrete gusts. Accuracy of the identie ed linear system models to the nonlinear plant is quantie ed with comparison of eigenvalues, the Vinnicombe gap metric, and time history matching. Results demonstrate that the observer/Kalman e lter identie cation method is suitable for aircraft online identie cation of locally linear aircraft models and is generally insensitive to moderate intensity Gaussian white sensor noise and for light to moderate intensity discrete gusts.

Boom and Receptacle Autonomous Air Refueling Using Visual Snake Optical Sensor

Autonomous air refueling is an important capability for the future deployment of unmanned air vehicles, because it permits unmanned air vehicles to be ferried in flight to overseas theaters of operation instead of being shipped unassembled in containers. This paper demonstrates the feasibility of precise and reliable boom and receptacle autonomous air refueling, without a human operator or supervisor, for nonmicrosized unmanned air vehicles. The system is composed of a vision sensor based on active deformable contour algorithms (visual snakes) and its relative navigation system integrated with a boom controller. The sensor camera is mounted on the tanker aircraft near the boom and images a single passive target image painted near the refueling receptacle on a receiver unmanned air vehicle. Controllers are developed in the paper for the refueling boom, and the stationkeeping controllers of the receiver unmanned air vehicle and tanker aircraft Performance and feasibility of the total system is demonstrated by simulated docking maneuvers in the presence of various levels of turbulence. Results presented in the paper show that the integrated sensor and controller enables precise boom and receptacle air refueling, including consideration.

Digital Autoland Control Laws Using Quantitative Feedback Theory and Direct Digital Design

of several aircraft problems, but not for outer-loop control or for automatic landing. This paper describes the synthesis and development of an automatic landing controller for medium-sized unmanned aerial vehicles, using discrete quantitative feedback theory. Controllers for the localizer, glideslope tracker, and automatic flare are developed, with a focus on outer-loop synthesis and robustness with respect to model uncertainty. Linear, nonreal-time, six-degree-of-freedom Monte Carlo simulation is used to compare the quantitative feedback theory controller with a baseline proportional–integral controller in several still-air and turbulent-air landing scenarios. Results presented in the paper show that the quantitative feedback theory controller provides superior performance robustness to the proportional–integral controller in turbulent-air conditions when model uncertainties are present. It is therefore concluded to be a promising candidate for an autoland controller for unmanned air vehicles.