Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

Temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle were generated by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method. The vehicle was assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. The aircraft model included fight dynamics, aerodynamics, and thermal constraints. This model was incorporated into an optimal control formulation that includes constraints on both the vehicle as well as mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. Optimal trajectories were be developed using several different performance costs in the optimal control formulation--minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrated that optimal trajectories that meet specified mission parameters and constraints can be determined and used for larger-scale operational and campaign planning

Trajectory optimization and guidance law development for national aerospace plane applications

The work completed to date is comprised of the following: a simple vehicle model representative of the aerospace plane concept in the hypersonic flight regime, fuel-optimal climb profiles for the unconstrained and dynamic pressure constrained cases generated using a reduced order dynamic model, an analytic switching condition for transition to rocket powered flight as orbital velocity is approached, simple feedback guidance laws for both the unconstrained and dynamic pressure constrained cases derived via singular perturbation theory and a nonlinear transformation technique, and numerical simulation results for ascent to orbit in the dynamic pressure constrained case

Pterodactyl: The Development and Performance of Guidance Algorithms for a Mechanically Deployed Entry Vehicle

Pterodactyl is a NASA Space Technology Mission Directorate (STMD) project focused on developing a design capability for optimal, scalable, Guidance and Control (G&C) solutions that enable precision targeting for Deployable Entry Vehicles (DEVs). This feasibility study is unique in that it focuses on the rapid integration of targeting performance analysis with structural & packaging analysis, which is especially challenging for new vehicle and mission designs. This paper will detail the guidance development and trajectory design process for a lunar return mission, selected to stress the vehicle designs and encourage future scalability. For the five G&C configurations considered, the Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) was selected for configurations requiring bank angle guidance and FNPEG with Uncoupled Range Control (URC) was developed for configurations requiring angle of attack and sideslip angle guidance. Successful G&C configurations are defined as those that can deliver payloads to the intended descent and landing initiation point, while abiding by trajectory constraints for nominal and dispersed trajectories

Automated flight test management system

The Phase 1 development of an automated flight test management system (ATMS) as a component of a rapid prototyping flight research facility for artificial intelligence (AI) based flight concepts is discussed. The ATMS provides a flight engineer with a set of tools that assist in flight test planning, monitoring, and simulation. The system is also capable of controlling an aircraft during flight test by performing closed loop guidance functions, range management, and maneuver-quality monitoring. The ATMS is being used as a prototypical system to develop a flight research facility for AI based flight systems concepts at NASA Ames Dryden

Assessment of flying-quality criteria for air-breathing aerospacecraft

A study of flying quality requirements for air breathing aerospacecraft gives special emphasis to the unusual operational requirements and characteristics of these aircraft, including operation at hypersonic speed. The report considers distinguishing characteristics of these vehicles, including dynamic deficiencies and their implications for control. Particular emphasis is given to the interaction of the airframe and propulsion system, and the requirements for dynamic systems integration. Past operational missions are reviewed to define tasks and maneuvers to be considered for this class of aircraft. Areas of special concern with respect to vehicle dynamics and control are identified. Experience with the space shuttle orbiter is reviewed with respect to flight control system mechanization and flight experience in approach and landing flying qualities for the National Aerospace Plane (NASP)

Remote Infrared Imaging of the Space Shuttle During Hypersonic Flight: HYTHIRM Mission Operations and Coordination

The Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project has been responsible for obtaining spatially resolved, scientifically calibrated in-flight thermal imagery of the Space Shuttle Orbiter during reentry. Starting with STS-119 in March of 2009 and continuing through to the majority of final flights of the Space Shuttle, the HYTHIRM team has to date deployed during seven Shuttle missions with a mix of airborne and ground based imaging platforms. Each deployment of the HYTHIRM team has resulted in obtaining imagery suitable for processing and comparison with computational models and wind tunnel data at Mach numbers ranging from over 18 to under Mach 5. This paper will discuss the detailed mission planning and coordination with the NASA Johnson Space Center Mission Control Center that the HYTHIRM team undergoes to prepare for and execute each mission

Large Scale Constrained Trajectory Optimization Using Indirect Methods

State-of-the-art direct and indirect methods face significant challenges when solving large scale constrained trajectory optimization problems. Two main challenges when using indirect methods to solve such problems are difficulties in handling path inequality constraints, and the exponential increase in computation time as the number of states and constraints in problem increases. The latter challenge affects both direct and indirect methods. A methodology called the Integrated Control Regularization Method (ICRM) is developed for incorporating path constraints into optimal control problems when using indirect methods. ICRM removes the need for multiple constrained and unconstrained arcs and converts constrained optimal control problems into two-point boundary value problems. Furthermore, it also addresses the issue of transcendental control law equations by re-formulating the problem so that it can be solved by existing numerical solvers for two-point boundary value problems (TPBVP). The capabilities of ICRM are demonstrated by using it to solve some representative constrained trajectory optimization problems as well as a five vehicle problem with path constraints. Regularizing path constraints using ICRM represents a first step towards obtaining high quality solutions for highly constrained trajectory optimization problems which would generally be considered practically impossible to solve using indirect or direct methods. The Quasilinear Chebyshev Picard Iteration (QCPI) method builds on prior work and uses Chebyshev Polynomial series and the Picard Iteration combined with the Modified Quasi-linearization Algorithm. The method is developed specifically to utilize parallel computational resources for solving large TPBVPs. The capabilities of the numerical method are validated by solving some representative nonlinear optimal control problems. The performance of QCPI is benchmarked against single shooting and parallel shooting methods using a multi-vehicle optimal control problem. The results demonstrate that QCPI is capable of leveraging parallel computing architectures and can greatly benefit from implementation on highly parallel architectures such as GPUs. The capabilities of ICRM and QCPI are explored further using a five-vehicle constrained optimal control problem. The scenario models a co-operative, simultaneous engagement of two targets by five vehicles. The problem involves 3DOF dynamic models, control constraints for each vehicle and a no-fly zone path constraint. Trade studies are conducted by varying different parameters in the problem to demonstrate smooth transition between constrained and unconstrained arcs. Such transitions would be highly impractical to study using existing indirect methods. The study serves as a demonstration of the capabilities of ICRM and QCPI for solving large-scale trajectory optimization methods. An open source, indirect trajectory optimization framework is developed with the goal of being a viable contender to state-of-the-art direct solvers such as GPOPS and DIDO. The framework, named beluga, leverages ICRM and QCPI along with traditional indirect optimal control theory. In its current form, as illustrated by the various examples in this dissertation, it has made significant advances in automating the use of indirect methods for trajectory optimization. Following on the path of popular and widely used scientific software projects such as SciPy [1] and Numpy [2], beluga is released under the permissive MIT license [3]. Being an open source project allows the community to contribute freely to the framework, further expanding its capabilities and allow faster integration of new advances to the state-of-the-art

Trajectory Optimization and Guidance Design by Convex Programming

The field of aerospace guidance and control has recently been evolving from focusing on traditional laws and controllers to numerical algorithms with the aim of achieving onboard applications for autonomous vehicle systems. However, it is very difficult to perform complex guidance and control missions with highly nonlinear dynamic systems and many constraints onboard. In recent years, an emerging trend has occurred in the field of Computational Guidance and Control (CG&C). By taking advantage of convex optimization and highly efficient interior point methods, CG&C allows complicated guidance and control problems to be solved in real time and offers great potential for onboard applications. With the significant increase in computational efficiency, convex-optimization-based CG&C is expected to become a fundamental technology for system autonomy and autonomous operations. In this dissertation, successive convex approaches are proposed to solve optimal control programs associated with aerospace guidance and control, and the emphasis is placed on potential onboard applications. First, both fuel-optimal and time-optimal low-thrust orbit transfer problems are investigated by a successive second-order cone programming method. Then, this convex method is extended and improved to solve hypersonic entry trajectory optimization problems by taking advantage of line-search and trust-region techniques. Finally, the successive convex approach is modified to the design of autonomous entry guidance algorithms. Simulation results indicate that the proposed methodologies are capable of generating accurate solutions for low-thrust orbit transfer problems and hypersonic entry problems with fast computational speed. The proposed methods have great potential for onboard applications

Paving the Way: The Influence of Early Research and Development Programs on Apollo, Saturn, and Legacy System Development

As we celebrate the 50th anniversary of the first successful human landings on the surface of the Moon in 1969, it is insightful to review the many historic accomplishments that contributed to this astounding human achievement. While the Apollo Program officially began following the charge by United States President John F. Kennedy in 1961, much of the foundation for Apollo was already underway with early research and development that began as early as the close of the second World War. Innovations and key decisions prior to the formal initiation of the Apollo Program, and even prior to the formation of the National Aeronautics and Space Administration (NASA), enabled the relatively rapid development of the Saturn V rocket, the Apollo capsule, and the Lunar Lander systems needed to achieve the goal of landing humans on the Moon and returning them safely to Earth by the close of the 1960s