RESULTS OF STUDIES ON A TWIN-GYRO ATTITUDE CONTROL SYSTEM FOR SPACE VEHICLES
Automatic closed loop and pilot operated twin-gyro systems are discussed as attitude stabilizers for large space vehicles
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Automatic closed loop and pilot operated twin-gyro systems are discussed as attitude stabilizers for large space vehicles
Wind profile developed for calculation of deflection impulse for rocket with liquid injection thrust vector control
The digital program ASTP Docking Dynamics as outlined is intended to aid the engineer using the program to determine the docking system loads and attendant vehicular motion resulting from docking two vehicles that have an androgynous, six-hydraulic-attenuator, guide ring, docking interface similar to that designed for the Apollo/Soyuz Test Project (ASTP). This program is set up to analyze two different vehicle combinations: the Apollo CSM docking to Soyuz and the shuttle orbiter docking to another orbiter. The subroutine modifies the vehicle control systems to describe one or the other vehicle combinations; the rest of the vehicle characteristics are changed by input data. To date, the program has been used to predict and correlate ASTP docking loads and performance with docking test program results from dynamic testing. The program modified for use on IBM 360 computers. Parts of the original docking system equations in the areas of hydraulic damping and capture latches are modified to better describe the detail design of the ASTP docking system.
Video-sensor/electronic-feedback control system being developed to provide automatic control of final stage of approach of active vehicle to passive vehicle or object. No communication between vehicles necessary. Docking target, mounted on post on passive vehicle, has three reflective dots, positions of which measured in image to determine relative position and orientation of target and vehicle. Control channels process video-sensor feedback into motion-control signals (thrustor commands in spacecraft or motor commands in robot). Conceived for use aboard chasing spacecraft to control its maneuvers in docking with chased spacecraft, concept also useful in controlling coupling of aircraft in flight or vessels on water or in controlling approach of robot to object to be manipulated.
A climate control system for vehicles includes an internal combustion engine that may be coupled to selectively power a first motor generator, and an air conditioning compressor that may be selectively powered by one or both of the first motor generator and a second motor generator, or by the internal combustion engine. The system may include a rechargeable battery, and a vehicle controller having a vehicle state circuit structured to determine a vehicle operating condition value and a state-of-charge value of the rechargeable battery, and a coupling determination circuit structured to provide an internal combustion engine-first motor generator coupling command in response to the vehicle operating condition value and the state-of-charge value. In response to the internal combustion engine-first motor generator coupling command being provided as coupled, the internal combustion engine may power the first motor generator.
In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.
Effect of liftoff dynamics on launch vehicle stability and control
Adaptive control systems for stabilizing structural bending modes of Saturn V launch vehicle
Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.
Longitudinal vehicle motion control is essential for enhancing performance and optimizing a vehicle’s energy usage. However, it remains a challenging task due to the nonlinear and uncertain nature of vehicle dynamics, along with varying driving conditions. This paper presents a novel ultra-local optimal control approach based on Pontryagin’s Minimum Principle (PMP) that circumvents the need for detailed system identification by employing an ultra-local model. The control objective is to minimize the total energy consumption under boundary conditions while ensuring smooth traction force generation. The proposed approach is evaluated using a high-fidelity vehicle model in three representative scenarios: (i) nominal driving, (ii) a change in tire road friction coefficient (TRFC) from 0.5 to 0.65 and road slope from 0% to 5% during the maneuver, with target velocity unchanged, and (iii) a change in target velocity from 20 m/s to 0 m/s during the maneuver, while maintaining nominal TRFC and slope conditions. The simulation results demonstrate that the proposed method delivers robust performance, effectively balancing consumption and tracking accuracy in all tested scenarios.
This paper summarizes the Adaptive Augmenting Control (AAC) flight characterization experiments performed using an F/A-18 (TN 853). AAC was designed and developed specifically for launch vehicles, and is currently part of the baseline autopilot design for NASA's Space Launch System (SLS). The scope covered here includes a brief overview of the algorithm (covered in more detail elsewhere), motivation and benefits of flight testing, top-level SLS flight test objectives, applicability of the F/A-18 as a platform for testing a launch vehicle control design, test cases designed to fully vet the AAC algorithm, flight test results, and conclusions regarding the functionality of AAC. The AAC algorithm developed at Marshall Space Flight Center is a forward loop gain multiplicative adaptive algorithm that modifies the total attitude control system gain in response to sensed model errors or undesirable parasitic mode resonances. The AAC algorithm provides the capability to improve or decrease performance by balancing attitude tracking with the mitigation of parasitic dynamics, such as control-structure interaction or servo-actuator limit cycles. In the case of the latter, if unmodeled or mismodeled parasitic dynamics are present that would otherwise result in a closed-loop instability or near instability, the adaptive controller decreases the total loop gain to reduce the interaction between these dynamics and the controller. This is in contrast to traditional adaptive control logic, which focuses on improving performance by increasing gain. The computationally simple AAC attitude control algorithm has stability properties that are reconcilable in the context of classical frequency-domain criteria (i.e., gain and phase margin). The algorithm assumes that the baseline attitude control design is well-tuned for a nominal trajectory and is designed to adapt only when necessary. Furthermore, the adaptation is attracted to the nominal design and adapts only on an as-needed basis (see Figure 1). The MSFC algorithm design was formulated during the Constellation Program and reached a high maturity level during SLS through simulation-based development and internal and external analytical review. The AAC algorithm design has three summary-level objectives: (1) "Do no harm;" return to baseline control design when not needed, (2) Increase performance; respond to error in ability of vehicle to track command, and (3) Regain stability; respond to undesirable control-structure interaction or other parasitic dynamics. AAC has been successfully implemented as part of the Space Launch System baseline design, including extensive testing in high-fidelity 6-DOF simulations the details of which are described in [1]. The Dryden Flight Research Center's F/A-18 Full-Scale Advanced Systems Testbed (FAST) platform is used to conduct an algorithm flight characterization experiment intended to fully vet the aforementioned design objectives. FAST was specifically designed with this type of test program in mind. The onboard flight control system has full-authority experiment control of ten aerodynamic effectors and two throttles. It has production and research sensor inputs and pilot engage/disengage and real-time configuration of up to eight different experiments on a single flight. It has failure detection and automatic reversion to fail-safe mode. The F/A-18 aircraft has an experiment envelope cleared for full-authority control and maneuvering and exhibits characteristics for robust recovery from unusual attitudes and configurations aided by the presence of a qualified test pilot. The F/A-18 aircraft has relatively high mass and inertia with exceptional performance; the F/A-18 also has a large thrust-to-weight ratio, owing to its military heritage. This enables the simulation of a portion of the ascent trajectory with a high degree of dynamic similarity to a launch vehicle, and the research flight control system can simulate unstable longitudinal dynamics. Parasitic dynamics such as slosh and bending modes, as well as atmospheric disturbances, are being produced by the airframe via modification of bending filters and the use of secondary control surfaces, including leading and trailing edge flaps, symmetric ailerons, and symmetric rudders. The platform also has the ability to inject signals in flight to simulate structural mode resonances or other challenging dynamics. This platform also offers more test maneuvers and longer maneuver times than a single rocket or missile test, which provides ample opportunity to fully and repeatedly exercise all aspects of the algorithm. Prior to testing on an F/A-18, AAC was the only component of the SLS autopilot design that had not been flight tested. The testing described in this paper raises the Technology Readiness Level (TRL) early in the SLS Program and is able to demonstrate its capabilities and robustness in a flight environment.
This dataset provides the following on road testing data: - Videos - In-vehicle dash camera videos during different testing scenarios. - Signal controller data - NTCIP log data and processed signal timing data from the corresponding signal controllers - Vehicle data - Vehicle data recorded during the testing, including GNSS, communication, CAN signals.
Phase I of a joint Department of Energy/Jet Propulsion Laboratory Program undertook the development of the Hybrid Test Vehicle (HTV), which has subsequently progressed through design, fabrication, and testing and evaluation phases. Attention is presently given to the design and test experience gained during the HTV development program, and a discussion is presented of the design features and performance capabilities of the various 'mule' vehicles, devoted to the separate development of engine microprocessor control, vehicle structure, and mechanical components, whose elements were incorporated into the final HTV design. Computer projections of the HTV's performance are given.
A system for real-time video image display for robotics or remote-vehicle teleoperation is described that has at least one robot arm or remotely operated vehicle controlled by an operator through hand-controllers, and one or more television cameras and optional lighting element. The system has at least one television monitor for display of a television image from a selected camera and the ability to select one of the cameras for image display. Graphics are generated with icons of cameras and lighting elements for display surrounding the television image to provide the operator information on: the location and orientation of each camera and lighting element; the region of illumination of each lighting element; the viewed region and range of focus of each camera; which camera is currently selected for image display for each monitor; and when the controller coordinate for said robot arms or remotely operated vehicles have been transformed to correspond to coordinates of a selected or nonselected camera.
A system for real-time video image display for robotics or remote-vehicle teleoperation is described that has at least one robot arm or remotely operated vehicle controlled by an operator through hand-controllers, and one or more television cameras and optional lighting element. The system has at least one television monitor for display of a television image from a selected camera and the ability to select one of the cameras for image display. Graphics are generated with icons of cameras and lighting elements for display surrounding the television image to provide the operator information on: the location and orientation of each camera and lighting element; the region of illumination of each lighting element; the viewed region and range of focus of each camera; which camera is currently selected for image display for each monitor; and when the controller coordinate for said robot arms or remotely operated vehicles have been transformed to correspond to coordinates of a selected or nonselected camera.
A Modular Autonomous Robotic System is being developed to convert any vehicle to autonomous control.
Control surface seals are crucial to current and future space vehicles, as they are used to seal the gaps surrounding body flaps, elevons, and other actuated exterior surfaces. During reentry, leakage of high temperature gases through these gaps could damage underlying lower temperature structures such as rudder drive motors and mechanical actuators, resulting in impaired vehicle control. To be effective, control surface seals must shield lower temperature structures from heat transfer by maintaining sufficient resiliency to remain in contact with opposing sealing surfaces through multiple compression cycles. The current seal exhibits significant loss of resiliency after a few compression cycles at elevated temperatures (i.e., 1900 F) and therefore would be inadequate for advanced space vehicles. This seal utilizes a knitted Inconel X-750 spring tube as its primary resilient element. As part of a larger effort to enhance seal resiliency, researchers at the NASA Glenn Research Center performed high temperature compression testing (up to 2000 F) on candidate spring tube designs employing material substitutions and modified geometries. These tests demonstrated significant improvements in spring tube resiliency (5.5x better at 1750 F) through direct substitution of heat treated Rene 41 alloy in the baseline knit design. The impact of geometry modification was minor within the range of parameters tested, however trends did suggest that moderate resiliency improvements could be obtained by optimizing the current spring tube geometry.
Failure or degradation of the flight control system, or hull damage, can lead to loss of vehicle control during entry. Possible failure scenarios are debris impact and wing damage that could result in a large aerodynamic asymmetry which cannot be trimmed out without additional yaw control. Currently the space shuttle uses aerodynamic control surfaces and Reaction Control System jets to control attitude. The forward jets are used for orbital maneuvering only, while the aft jets are used for yaw control during entry. This paper develops a controller for using the forward reaction control system jets as an additional control during entry, and assesses its value and feasibility during failure situations. Forward-aft jet blending logic is created, and implemented on a simplified model of the space shuttle entry flight control system. The model is validated and verified on the nonlinear, six degree-of-freedom Shuttle Engineering Simulator. A rudimentary human factors study was undertaken using the forward cockpit simulator at Johnson Space Center, to assess flying qualities of the new system and pilot workload. Results presented in the paper show that the combination of forward and aft jets provides useful additional yaw control, in addition to potential fuel savings and the ability to balance the use of the fuel in the forward and aft tanks to meet availability constraints of both forward and aft fuel tanks. Piloted simulation studies indicated that using both sets of jets while flying a damaged space shuttle reduces pilot workload, and makes the vehicle more responsive.