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At least 271 records · Page 15

Robotic-Vehicle Perception Control For Detecting Obstacles

Obstacle-detection systems designed to make most of limited data-processing resources. Bump or step identified, from stereoscopic images of scene ahead, by obstacle-detection algorithm. If bump or step exceeds specified step height, marked as obstacle, and control actions taken to avoid obstacle.

Grandjean, Pierrick C.↗

Boeing Crew Exploration Vehicle Environmental Control and Life Support System Architecture Overview

The Boeing Company under the teaming agreement with the Northrop Grumman Systems Corporation and in compliance with the NASA Phase 1 contract, had the responsibilities for the CEV architecture development of the Environmental control and life support (ECLS) system under the NASA Phase 1 contract. The ECLS system was comprised of the various subsystems which provided for a shirt-sleeve habitable environment for crew to live and work in the crew module of the CEV. This architecture met the NASA requirements to ferry cargo and crew to ISS, and Lunar sortie missions, with extensibility to long duration missions to Moon and MARS. This paper provides a summary overview of the CEV ECLS subsystems which was proposed in compliance with the contract activities.

Saiidi, Mo↗

Ultra-Compact Neuroprocessor for Automotive Diagnostic and Control

Demands on the performance of vehicle control and diagnostic systems are steadily increasing as a consequence of stiff global competition and government mandates. In the United States, light trucks and passenger cars are required both to meet strict emission standards and to perform continuous diagnostics of all emissions systems operating in the vehicle.

Neuroprocessor automotive diagnostics↗

Control and Simulation of a Deployable Entry Vehicle with Aerodynamic Control Surfaces

In this paper, we investigate the static stability of a deployable entry vehicle called the Lifting Nano-ADEPT and design a control system to follow bank angle, angle-of-attack, and sideslip guidance commands. The control design, based on linear quadratic regulator optimal techniques, utilizes aerodynamic control surfaces to track angle-of-attack, sideslip angle, and bank angle commands. We demonstrate, using a nonlinear simulation environment, that the controller is able to accurately track step commands that may come from a guidance algorithm.

Margolis, Benjamin W. L.↗

Flight Performance and Stability of Space Launch System Core Stage Thrust Vector Control

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. The Core Stage TVC shares vehicle control authority with the SLS 5-segment Solid Rocket Boosters (SRBs) during boost phase flight, and is the sole means of vehicle flight control during in exoatmospheric flight following SRB separation. TVC responses during Green Run Hot Fire (GRHF) testing revealed that the TVC did not meet its performance specifications. Step and frequency responses exhibited unexpected departures from prior laboratory data and modeled behavior. Post-test analysis determined that the characteristics of the structure and gimbal friction are significantly influenced by the thrust-loaded conditions, and the command avionics exhibited a small but important gain nonlinearity. Using the available test data, the design team augmented the flight control TVC models to bound the observed results and include the additional fidelity needed for vehicle flight control analysis so as to build sufficient rationale for flight certification. Prior to the Green Run tests, “simplex” linear models typically used for flight control analysis did not include gimbal friction and other nonlinearities owing to long-standing assumptions that these effects were negligible in the Shuttle Orbiter TVC system. Following the Green Run findings, simulation analysis of the flight dynamics in the time and frequency domain revealed the propensity for a flight control limit cycle oscillation (LCO) if friction and structural compliances fell near the edges of test-predicted bounds. While the “most probable” models did not predict an in-flight LCO, the SLS Program conservatively proceeded with a system-wide evaluation and ultimate acceptance of the possibility for a small amplitude, low-frequency TVC LCO in flight. A final validation of the extensive test and modeling effort occurred when the first flight of SLS successfully demonstrated the fully integrated performance of the vehicle’s TVC system This paper is the final installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, the development of flight rationale in light of the TVC responses observed in Green Run is discussed, along with a review of the flight telemetry illustrating the correlation of the preflight predictions with the observed performance.

John H. Wall↗

Applications of Payload Directed Flight

Next generation aviation flight control concepts require autonomous and intelligent control system architectures that close control loops directly around payload sensors in manner more integrated and cohesive that in traditional autopilot designs. Research into payload directed flight control at NASA Ames Research Center is investigating new and novel architectures that can satisfy the requirements for next generation control and automation concepts for aviation. Tighter integration between sensor and machine requires definition of specific sensor-directed control modes to tie the sensor data directly into a vehicle control structures throughout the entire control architecture, from low-level stability- and control loops, to higher level mission planning and scheduling reasoning systems. Payload directed flight systems can thus provide guidance, navigation, and control for vehicle platforms hosting a suite of onboard payload sensors. This paper outlines related research into the field of payload directed flight; and outlines requirements and operating concepts for payload directed flight systems based on identified needs from the scientific literature.'

Ippolito, Corey↗

"Fly-by-Wireless": A Revolution in Aerospace Vehicle Architecture for Instrumentation and Control

Aerospace vehicle programs have always counted on the cables and connectors to provide power, grounding, data and time synchronization throughout a vehicle's life-cycle. Even with numerous improvements, wiring and connector problems and sensors continue to be key failure points, causing many hours of troubleshooting and replacement. Costly flight delays have been precipitated by the need to troubleshoot cables/connections, and/or repair a sensor. Wiring continues to be too expensive to remove once it is installed, even with the weight penalties. Miles of test instrumentation and low flight sensor wires still plague the aerospace industry. New technology options for data connectivity, processing and micro/nano manufacturing are making it possible to retrofit existing vehicles, like the Space Shuttle. New vehicles can now develop architectures that provide for and take advantage of alternatives to wired connectivity. This project motivates the aerospace industry and technology providers to establish: (1) A new emphasis for system engineering approaches to reduce cables and connectors. (2) Provisions for modularity and accessibility in the vehicle architecture. (3) A set of technologies that support alternatives to wired connectivity.

Studor, George↗

Pterodactyl: Guidance and Control of a Symmetric Deployable Entry Vehicle using an Aerodynamic Control System

The NASA-funded Pterodactyl project seeks to advance the state-of-the-art for varying entry vehicle types by developing unconventional guidance and control technologies for Deployable Entry Vehicles (DEVs) that can be applied to different entry vehicle configurations. Prior work by the authors [1–5] involved developing both traditional and novel integrated guidance and control solutions for a Pterodactyl Baseline Vehicle (PBV), a variant of an asymmetric DEV called the Lifting Nano ADEPT (LNA) [6]. In the prior studies, two different guidance schemes were designed and implemented for the PBV: (i) traditional bank angle guidance developed using the Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) and (ii) novel angle of attack and sideslip (α - β) guidance developed using FNPEG with Uncoupled Range Control [4]. Using Linear Quadratic Regulator (LQR) optimal control methods with state-feedback integral control designs, these guidance trajectories were designed to be tracked using (i) a conventional propulsive entry vehicle control hardware architecture - reaction control systems (RCS) and (ii) novel non-propulsive entry vehicle control systems - aerodynamic flap control system (FCS) and moving mass control system (MMCS) [1]. The novel FCS and MMCS architectures were designed to track α - β guidance commands while the RCS was designed to track bank angle commands. It was discovered that the asymmetric DEV, the PBV, experienced a non-zero induced roll moment due to sideslip that the FCS and MMCS architectures had limited capability to trim out. These two architectures were designed to provide independent angle of attack and sideslip commands with limited consideration for roll moment generation to trim. As a result, for the PBV, the FCS and MMCS configurations as designed, were limited in providing the control authority needed to track an α - β guidance trajectory [1]. These results form the motivation for the work presented in this paper - utilizing an aerodynamic control system to track α - β guidance commands for a symmetric DEV with the expectation that a symmetric entry vehicle will have zero or significantly reduced roll moment due to sideslip that the FCS can handle when tracking an α - β guidance trajectory. To demonstrate the feasibility of a novel guidance and control architecture on a DEV, we utilize a symmetric DEV, the PBV-II, for (i) the novel α - β guidance development using FNPEG with Uncoupled Range Control and (ii) LQR control design using eight aerodynamic control surfaces. This paper demonstrates that the novel uncoupled α - β guidance tracking can be achieved using aerodynamic control surfaces on a symmetric deployable entry vehicle configuration.

Wendy A Okolo↗

Lunar Vehicle Active Charge Control System (LVACCS)+

The Lunar Vehicle Active Charge Control System (LVACCS) is an instrument in development that will measure the electrical potential of a spacecraft or rover under both positive and negative charge conditions, actively discharge negative charge, and charge the vehicle to a safe positive potential. All surfaces immersed in a plasma charge to non-zero potentials. In very low-density plasma (< 100 cm^-3), space vehicle charging can interfere with plasma probe measurements, degrade avionics performance, or cause a total system failure. LVACCS provides real-time in-situ space situational awareness that overcome these challenges in a small package. LVACCS has been awarded a NASA PICASSO grant to bring the instrument to technology readiness level 5. LVACCS consists of two main components: a collimated photoelectron gun (CPEG) and a Spacecraft Charge Detector (SCD).Monitoring charge build up on the lunar surface isa critical first step to understand hazards for crew, rovers, and instrumentation operating there.The LVACCS instrument will be able to fill in this gap providing robust lunar surface potential measurements and active charge dissipation.

Moon↗

Remote optical wind detection and aerodynamic control system for ground vehicle

An aerodynamic control system for a ground vehicle comprises a LiDAR module including at least one LiDAR sensor configured to obtain wind data upstream of the ground vehicle; a computing device; an aerodynamic device controller; and an aerodynamic device including a control surface. The computing device is configured to receive the wind data from the LiDAR module and generate output signals based on the wind data. The aerodynamic device controller is configured to receive the output signals from the computing device and generate control signals to control the aerodynamic device to adjust aerodynamic properties of the ground vehicle based at least in part the wind data. Changes to the configuration of the control surface may include increasing or decreasing a deflection angle of the at least one aerodynamic device. The aerodynamic device may include, e.g., a pneumatically actuated aerodynamic device or an electro-mechanically actuated aerodynamic device.

Damon, Kenneth H.↗

Robust, Practical Adaptive Control for Launch Vehicles

A modern mechanization of a classical adaptive control concept is presented with an application to launch vehicle attitude control systems. Due to a rigorous flight certification environment, many adaptive control concepts are infeasible when applied to high-risk aerospace systems; methods of stability analysis are either intractable for high complexity models or cannot be reconciled in light of classical requirements. Furthermore, many adaptive techniques appearing in the literature are not suitable for application to conditionally stable systems with complex flexible-body dynamics, as is often the case with launch vehicles. The present technique is a multiplicative forward loop gain adaptive law similar to that used for the NASA X-15 flight research vehicle. In digital implementation with several novel features, it is well-suited to application on aerodynamically unstable launch vehicles with thrust vector control via augmentation of the baseline attitude/attitude-rate feedback control scheme. The approach is compatible with standard design features of autopilots for launch vehicles, including phase stabilization of lateral bending and slosh via linear filters. In addition, the method of assessing flight control stability via classical gain and phase margins is not affected under reasonable assumptions. The algorithm s ability to recover from certain unstable operating regimes can in fact be understood in terms of frequency-domain criteria. Finally, simulation results are presented that confirm the ability of the algorithm to improve performance and robustness in realistic failure scenarios.

Orr, Jeb. S.↗

Independent Orbiter Assessment (IOA): Analysis of the guidance, navigation, and control subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) is presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results corresponding to the Orbiter Guidance, Navigation, and Control (GNC) Subsystem hardware are documented. The function of the GNC hardware is to respond to guidance, navigation, and control software commands to effect vehicle control and to provide sensor and controller data to GNC software. Some of the GNC hardware for which failure modes analysis was performed includes: hand controllers; Rudder Pedal Transducer Assembly (RPTA); Speed Brake Thrust Controller (SBTC); Inertial Measurement Unit (IMU); Star Tracker (ST); Crew Optical Alignment Site (COAS); Air Data Transducer Assembly (ADTA); Rate Gyro Assemblies; Accelerometer Assembly (AA); Aerosurface Servo Amplifier (ASA); and Ascent Thrust Vector Control (ATVC). The IOA analysis process utilized available GNC hardware drawings, workbooks, specifications, schematics, and systems briefs for defining hardware assemblies, components, and circuits. Each hardware item was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Trahan, W. H.↗