Real-time optimal guidance.
Repetitive in-flight calculation of optimal rocket guidance using algorithm method for solving boundary value problem
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Repetitive in-flight calculation of optimal rocket guidance using algorithm method for solving boundary value problem
Real time computer control system queueing model to optimize preemptible and nonpreemptible job priority assignment
NASA has ambitious plans to send astronaut crews to the south polar region of the Moon and explore this lunar terrain with humans for the first time through a series of Artemis missions. Artemis will provide economic benefits, drive technological advancement, and inspire the next generation of explorers. Simultaneously, Artemis presents a unique opportunity for humans to conduct high-priority planetary science in situ in the south polar region of the Moon. Prior to human exploration, landed robotic precursor investigations can provide valuable information to reduce risk and maximize discovery and productivity of subsequent crewed missions. NASA’s Volatiles Investigating Polar Exploration Rover (VIPER) is a robotic mission designed to explore and characterize the lunar south polar region prior to crewed Artemis landed missions. VIPER is designed to explore multiple thermal regimes to characterize the lunar polar environment and regolith properties, and to explore for surface and subsurface ices. Each of these objectives are key for both scientific investigation and to detect and assess volatile deposits to support in situ resource utilization (ISRU) and a sustained human presence on the Moon. VIPER would also operate with a real-time mission operations architecture with relevance and feed-forward to Artemis crewed operations on the lunar surface. VIPER would provide key information regarding the lunar environment, scientific exploration, technologies, and real-time operations to optimize the valuable surface exploration time of Artemis crew members while simultaneously reducing risk to crew and increasing health and human safety on the lunar surface.
The requirements of a unified optimal guidance scheme are discussed, giving attention to a general formulation, aspects of self-targeting, problems of optimum guidance within the atmosphere, and a unified concept for all flight phases. Since no previous guidance scheme meets these requirements, the shuttle demands a fundamentally new approach. A new unified optimal guidance scheme, called Mascot, was developed. The capabilities of Mascot include the real-time solution of general trajectory-optimization problems and the unification of guidance for all flight phases.
The S-IVB stage with Instrument Unit (IU) has been successfully deorbited in the Pacific corridor following each launch of the Skylab crew. A description of the S-IVB hardware and the deorbit method includes an evaluation of stage capabilities and of stage conditions, propellant residuals, and available propellants required to provide the deorbit impulse. A significant feature of the method employs real-time monitoring of stage systems performance to optimize the timing of the deorbit sequence. Results of the deorbited flight stages are presented and compared to preflight and real-time determined available impulse and footprint.
A study was performed to determine the best design tube window and X-ray fluorescence analyzer for quantitative analysis of Venusian dust and condensates. The principal objective of the project was to develop the best counter tube window geometry for the sensing element of the instrument. This included formulation of a mathematical model of the window and optimization of its parameters. The proposed detector and instrument has several important features. The instrument will perform a near real-time analysis of dust in the Venusian atmosphere, and is capable of measuring dust layers less than 1 micron thick. In addition, wide dynamic measurement range will be provided to compensate for extreme variations in count rates. An integral pulse-height analyzer and memory accumulate data and read out spectra for detail computer analysis on the ground.
The industrial engineer is often required to design and implement control systems and organization for manufacturing and service facilities, to optimize quality, delivery, and yield, and minimize cost. Despite progress in computer science most such systems still employ human operators and managers as real-time control elements. Manual control theory should therefore be applicable to at least some aspects of industrial system design and operations. Formulation of adequate model structures is an essential prerequisite to progress in this area; since real-world production systems invariably include multilevel and multiloop control, and are implemented by timeshared human effort. A modular structure incorporating certain new types of functional element, has been developed. This forms the basis for analysis of an industrial process operation. In this case it appears that managerial controllers operate in a discrete predictive mode based on fast time modelling, with sampling interval related to plant dynamics. Successive aggregation causes reduced response bandwidth and hence increased sampling interval as a function of level.
The past century of passenger flight has seen continuous improvement in aviation safety by the aerospace industry. However, while commercial aviation accident rates have continued to decline, human error-related incident and accident rates remain remarkably constant across all types of aviation (Shappell, et al., 2007). Unfortunately, this level of human error is unacceptable when considering projections for increased traffic volume (FAA, 2009), and is likely to yield more incidents and accidents unless a more complete understanding of operator error is achieved and remediations are implemented. One area of interest highlighted by researchers is Hazardous States of Awareness (HSAs) that can result from deficiencies in the design and inappropriate use of human-machine interfaces. Identifying and mitigating HSAs is critical for reducing operator errors. One promising approach uses psychophysiological measures which enable automated systems to adapt to the operator?s state and modify modes of operation to support optimal human performance (Scerbo, 2007). This paper will survey previous research and describe future directions for the application of psychophysiological measures of operators derived from cortical and autonomic assessment to perform real-time adaptive modulation of human-automation task mode mixes. The authors will present a summary of previous work done at NASA LaRC and Old Dominion University using a Psychophysiologically Adaptive System (PAS) in which the level of automation of the NASA Multi-Attribute Task Battery was modulated based on Engagement Indices derived from the users? electroencephalogram (Pope, Bogart, & Bartolome, 1995; for review see, Scerbo, Freeman, & Mikulka, 2003). Future theoretical and methodological directions for this type of closed-loop research will be discussed. Specifically, the capacity for this type of PAS to maintain effective operator state and to enable validation of candidate physiological indices will be described. Consideration will also be given to critical system characteristics (e.g., engagement indices, methods for invoking changes among system states, individual differences among users, etc.) that have been or still need to be studied. The potential of the PAS approach for interactive system design and prototyping will also be described. Examples of adaptive automation flight deck concepts in recent experiments will be highlighted and discussed.
An algorithm employing a modified sequential random perturbation, or creeping random search, was applied to the problem of optimizing the parameters of a high-energy beam transport system. The stochastic solution of the mathematical model for first-order magnetic-field expansion allows the inclusion of state-variable constraints, and the inclusion of parameter constraints allowed by the method of algorithm application eliminates the possibility of infeasible solutions. The mathematical model and the algorithm were programmed for a real-time simulation facility; thus, two important features are provided to the beam designer: (1) a strong degree of man-machine communication (even to the extent of bypassing the algorithm and applying analog-matching techniques), and (2) extensive graphics for displaying information concerning both algorithm operation and transport-system behavior. Chromatic aberration was also included in the mathematical model and in the optimization process. Results presented show this method as yielding better solutions (in terms of resolutions) to the particular problem than those of a standard analog program as well as demonstrating flexibility, in terms of elements, constraints, and chromatic aberration, allowed by user interaction with both the algorithm and the stochastic model. Example of slit usage and a limited comparison of predicted results and actual results obtained with a 600 MeV cyclotron are given.
A three axis inertial system was packaged in an Apollo gimbal fixture for fine grain evaluation of strapdown system performance in dynamic environments. These evaluations have provided information to assess the effectiveness of real-time compensation techniques and to study system performance tradeoffs to factors such as quantization and iteration rate. The strapdown performance and tradeoff studies conducted include: (1) Compensation models and techniques for the inertial instrument first-order error terms were developed and compensation effectivity was demonstrated in four basic environments; single and multi-axis slew, and single and multi-axis oscillatory. (2) The theoretical coning bandwidth for the first-order quaternion algorithm expansion was verified. (3) Gyro loop quantization was identified to affect proportionally the system attitude uncertainty. (4) Land navigation evaluations identified the requirement for accurate initialization alignment in order to pursue fine grain navigation evaluations.
An approach to achieving an optimized set of crew/computer interface requirements on the Space Shuttle program is described. It consists of defining the mission phases and crew timelines, developing a functional description of the crew/computer interface displays and controls software, conducting real-time simulations using pilot evaluation of the interface displays and controls, and developing a set of crew/computer functional requirements specifications. The simulator is a two-man crew station which includes three CRTs with keyboards for simulating the crew/computer interface. The programs simulate the mission phases and the flight hardware, including the flight computer and CRT displays.
Combined optimal estimation and control techniques are applied for the first time to satellite tracking systems. Both radio antenna and optical tracking systems of NASA are considered. The optimal estimation is accomplished using an extended Kalman filter resulting in an estimated state of the satellite and of the tracking system. This estimated state constitutes an input to the optimal controller. The optimal controller treats a linearized system with a quadratic performance index. The maximum principle is applied and a steady-state approximation to the resulting Riccati equation is obtained. A computer program, RATS, implementing this algorithm is described. A feasibility study of real-time implementation, tracking simulations, and parameter sensitivity studies are also reported.
The problem of real-time estimation of a lifting reentry vehicle trajectory of the shuttle orbiter type is considered. Simulations feature large position and velocity uncertainties at radar acquisition and realistic model errors in lift, drag and other model parameters. Radar tracking and accelerometer data are simulated. Significant nonlinearities are found to exist on spacecraft acquisition. An iterated nonlinear filter is shown to perform optimally during the radar acquisition phase. An adaptive filter is shown to track time-varying model errors, such as errors in the lift and drag coefficients, down to the noise level. Such real-time model tracking (identification) is frequently required for guidance and control implementation.
An approach to calculating optimal, gliding flight paths of the type associated with the space shuttle's transition from entry to cruising flight is presented. Kinetic energy and total energy (per unit weight) replace velocity and time in the dynamic equations, reducing the dimension and complexity of the problem. The capability for treating integral and terminal penalties (as well as Mach number effects) is retained in the numerical optimization; hence, stability and control boundaries can be observed as trajectories to the desired final energy, flight path angle, and range are determined. Numerical results show that the 'jump' to the 'front-side of the L/D curve' need not be made until the end of the transition and that the dynamic model provides a conservative range estimate. Alternatives for real-time trajectory control are discussed.
Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.
During the Apollo 15 and 16 missions, a special camera provided the scientific community and the home viewer with real-time coverage of the lunar exploration. The lunar blast-off of the Apollo 16 ascent module was tracked by the mission controller at NASA's Manned Space Center and watched 250,000 miles away on earth. The operation of this television camera and the remote control unit are described and block diagrams given. Ground-command capability from the Mission Control Center permitted versatility and optimization of the TV coverage, without diverting the astronauts from their primary role of lunar exploration.
The control of merging aircraft is formulated as a finite-time, quadratic optimal control problem of a linear system with state and control constraints. The purpose of this paper is to demonstrate that the Hybrid Air Traffic Controller (HAC), which has been previously developed as a solution to this problem, may be easily implemented. Use is made of both the properties of the algebraic solution to the matrix Riccati equation and the structure of the linear model. This approach results in a real-time synthesis procedure for the HAC which does not rely on iterative numerical integration techniques.
Real time computer algorithm for achieving optimal position of tracking antenna with nonlinear control system