Search NASA⌕ Search

SEARCH · Search NASA

Results for “Control”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

A Framework for Optimal Control Allocation with Structural Load Constraints

Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

Frost, Susan A.↗
NASA NTRS2010

Adaptive Control of Flexible Structures Using Residual Mode Filters

Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

Balas, Mark J.↗
NASA NTRS2011

Implementation of Enhanced Propulsion Control Modes for Emergency Flight Operation

Aircraft engines can be effective actuators to help pilots avert or recover from emergency situations. Emergency control modes are being developed to enhance the engines performance to increase the probability of recovery under these circumstances. This paper discusses a proposed implementation of an architecture that requests emergency propulsion control modes, allowing the engines to deliver additional performance in emergency situations while still ensuring a specified safety level. In order to determine the appropriate level of engine performance enhancement, information regarding the current emergency scenario (including severity) and current engine health must be known. This enables the engine to operate beyond its nominal range while minimizing overall risk to the aircraft. In this architecture, the flight controller is responsible for determining the severity of the event and the level of engine risk that is acceptable, while the engine controller is responsible for delivering the desired performance within the specified risk range. A control mode selector specifies an appropriate situation-specific enhanced mode, which the engine controller then implements. The enhanced control modes described in this paper provide additional engine thrust or response capabilities through the modification of gains, limits, and the control algorithm, but increase the risk of engine failure. The modifications made to the engine controller to enable the use of the enhanced control modes are described, as are the interaction between the various subsystems and importantly, the interaction between the flight controller/pilot and the propulsion control system. Simulation results demonstrate how the system responds to requests for enhanced operation and the corresponding increase in performance.

Csank, Jeffrey T.↗
NASA NTRS2011

A Globally Stable Lyapunov Pointing and Rate Controller for the Magnetospheric MultiScale Mission (MMS)

The Magnetospheric MultiScale Mission (MMS) is scheduled to launch in late 2014. Its primary goal is to discover the fundamental plasma physics processes of reconnection in the Earth's magnetosphere. Each of the four MMS spacecraft is spin-stabilized at a nominal rate of 3 RPM. Traditional spin-stabilized spacecraft have used a number of separate modes to control nutation, spin rate, and precession. To reduce the number of modes and simplify operations, the Delta-H control mode is designed to accomplish nutation control, spin rate control, and precession control simultaneously. A nonlinear design technique, Lyapunov's method, is used to design the Delta-H control mode. A global spin rate controller selected as the baseline controller for MMS, proved to be insufficient due to an ambiguity in the attitude. Lyapunov's design method was used to solve this ambiguity, resulting in a controller that meets the design goals. Simulation results show the advantage of the pointing and rate controller for maneuvers larger than 90 deg and provide insight into the performance of this controller.

Shah, Neerav↗
NASA NTRS2011

Digital Interface Board to Control Phase and Amplitude of Four Channels

An increasing number of parts are designed with digital control interfaces, including phase shifters and variable attenuators. When designing an antenna array in which each antenna has independent amplitude and phase control, the number of digital control lines that must be set simultaneously can grow very large. Use of a parallel interface would require separate line drivers, more parts, and thus additional failure points. A convenient form of control where single-phase shifters or attenuators could be set or the whole set could be programmed with an update rate of 100 Hz is needed to solve this problem. A digital interface board with a field-programmable gate array (FPGA) can simultaneously control an essentially arbitrary number of digital control lines with a serial command interface requiring only three wires. A small set of short, high-level commands provides a simple programming interface for an external controller. Parity bits are used to validate the control commands. Output timing is controlled within the FPGA to allow for rapid update rates of the phase shifters and attenuators. This technology has been used to set and monitor eight 5-bit control signals via a serial UART (universal asynchronous receiver/transmitter) interface. The digital interface board controls the phase and amplitude of the signals for each element in the array. A host computer running Agilent VEE sends commands via serial UART connection to a Xilinx VirtexII FPGA. The commands are decoded, and either outputs are set or telemetry data is sent back to the host computer describing the status and the current phase and amplitude settings. This technology is an integral part of a closed-loop system in which the angle of arrival of an X-band uplink signal is detected and the appropriate phase shifts are applied to the Ka-band downlink signal to electronically steer the array back in the direction of the uplink signal. It will also be used in the non-beam-steering case to compensate for phase shift variations through power amplifiers. The digital interface board can be used to set four 5-bit phase shifters and four 5-bit attenuators and monitor their current settings. Additionally, it is useful outside of the closed-loop system for beamsteering alone. When the VEE program is started, it prompts the user to initialize variables (to zero) or skip initialization. After that, the program enters into a continuous loop waiting for the telemetry period to elapse or a button to be pushed. A telemetry request is sent when the telemetry period is elapsed (every five seconds). Pushing one of the set or reset buttons will send the appropriate command. When a command is sent, the interface status is returned, and the user will be notified by a pop-up window if any error has occurred. The program runs until the End Program button is depressed.

Smith, Amy E.↗
NASA NTRS2012

Experimental Studies of Low-Pressure Turbine Flows and Flow Control. Streamwise Pressure Profiles and Velocity Profiles

This report summarizes research performed in support of the NASA Glenn Research Center (GRC) Low-Pressure Turbine (LPT) Flow Physics Program. The work was performed experimentally at the U.S. Naval Academy faculties. The geometry corresponded to "Pak B" LPT airfoil. The test section simulated LPT flow in a passage. Three experimental studies were performed: (a) Boundary layer measurements for ten baseline cases under high and low freestream turbulence conditions at five Reynolds numbers of 25,000, 50,000, 100,000, 200,000, and 300,000, based on passage exit velocity and suction surface wetted length; (b) Passive flow control studies with three thicknesses of two-dimensional bars, and two heights of three-dimensional circular cylinders with different spanwise separations, at same flow conditions as the 10 baseline cases; (c) Active flow control with oscillating synthetic (zero net mass flow) vortex generator jets, for one case with low freestream turbulence and a low Reynolds number of 25,000. The Passive flow control was successful at controlling the separation problem at low Reynolds numbers, with varying degrees of success from case to case and varying levels of impact at higher Reynolds numbers. The active flow control successfully eliminated the large separation problem for the low Reynolds number case. Very detailed data was acquired using hot-wire anemometry, including single and two velocity components, integral boundary layer quantities, turbulence statistics and spectra, turbulent shear stresses and their spectra, and intermittency, documenting transition, separation and reattachment. Models were constructed to correlate the results. The report includes a summary of the work performed and reprints of the publications describing the various studies.This report summarizes research performed in support of the NASA Glenn Research Center (GRC) Low-Pressure Turbine (LPT) Flow Physics Program. The work was performed experimentally at the U.S. Naval Academy faculties. The geometry corresponded to "Pak B" LPT airfoil. The test section simulated LPT flow in a passage. Three experimental studies were performed: (a) Boundary layer measurements for ten baseline cases under high and low freestream turbulence conditions at five Reynolds numbers of 25,000, 50,000, 100,000, 200,000, and 300,000, based on passage exit velocity and suction surface wetted length; (b) Passive flow control studies with three thicknesses of two-dimensional bars, and two heights of three-dimensional circular cylinders with different spanwise separations, at same flow conditions as the 10 baseline cases; (c) Active flow control with oscillating synthetic (zero net mass flow) vortex generator jets, for one case with low freestream turbulence and a low Reynolds number of 25,000. The Passive flow control was successful at controlling the separation problem at low Reynolds numbers, with varying degrees of success from case to case and varying levels of impact at higher Reynolds numbers. The active flow control successfully eliminated the large separation problem for the low Reynolds number case. Very detailed data was acquired using hot-wire anemometry, including single and two velocity components, integral boundary layer quantities, turbulence statistics and spectra, turbulent shear stresses and their spectra, and intermittency, documenting transition, separation and reattachment. Models were constructed to correlate the results. The report includes a summary of the work performed and reprints of the publications describing the various studies. The folders in this supplement contain processed data in ASCII format. Streamwise pressure profiles and velocity profiles are included. The velocity profiles were acquired using single sensor and cross sensor hot-wire probes which were traversed from the wall to the freestream at various streamwise locations. In some of the flow control cases (3D Trips and Jets) profiles were acquired at multiple spanwise locations.

Volino, Ralph↗
NASA NTRS2013

Method and apparatus for automatic control of a humanoid robot

A robotic system includes a humanoid robot having a plurality of joints adapted for force control with respect to an object acted upon by the robot, a graphical user interface (GUI) for receiving an input signal from a user, and a controller. The GUI provides the user with intuitive programming access to the controller. The controller controls the joints using an impedance-based control framework, which provides object level, end-effector level, and/or joint space-level control of the robot in response to the input signal. A method for controlling the robotic system includes receiving the input signal via the GUI, e.g., a desired force, and then processing the input signal using a host machine to control the joints via an impedance-based control framework. The framework provides object level, end-effector level, and/or joint space-level control of the robot, and allows for functional-based GUI to simplify implementation of a myriad of operating modes.

Abdallah, Muhammad E↗
NASA NTRS2014

Design and Analysis of Morpheus Lander Flight Control System

The Morpheus Lander is a vertical takeoff and landing test bed vehicle developed to demonstrate the system performance of the Guidance, Navigation and Control (GN&C) system capability for the integrated autonomous landing and hazard avoidance system hardware and software. The Morpheus flight control system design must be robust to various mission profiles. This paper presents a design methodology for employing numerical optimization to develop the Morpheus flight control system. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics and propellant slosh. Under the assumption that the Morpheus time-varying dynamics and control system can be frozen over a short period of time, the flight controllers are designed to stabilize all selected frozen-time control systems in the presence of parametric uncertainty. Both control gains in the inner attitude control loop and guidance gains in the outer position control loop are designed to maximize the vehicle performance while ensuring robustness. The flight control system designs provided herein have been demonstrated to provide stable control systems in both Draper Ares Stability Analysis Tool (ASAT) and the NASA/JSC Trick-based Morpheus time domain simulation.

Jang, Jiann-Woei↗
NASA NTRS2014

Re-Engineering the ISS Payload Operations Control Center During Increased Utilization and Critical Onboard Events

With an increase in utilization and hours of payload operations being executed onboard the International Space Station (ISS), upgrading the NASA Marshall Space Flight Center (MSFC) Huntsville Operations Support Center (HOSC) ISS Payload Control Area (PCA) was essential to gaining efficiencies and assurance of current and future payload health and science return. PCA houses the Payload Operations Integration Center (POIC) responsible for the execution of all NASA payloads onboard the ISS. POIC Flight Controllers are responsible for the operation of voice, stowage, command, telemetry, video, power, thermal, and environmental control in support of ISS science experiments. The methodologies and execution of the PCA refurbishment were planned and performed within a four-month period in order to assure uninterrupted operation of ISS payloads and minimal impacts to payload operations teams. To vacate the PCA, three additional HOSC control rooms were reconfigured to handle ISS real-time operations, Backup Control Center (BCC) to Mission Control in Houston, simulations, and testing functions. This involved coordination and cooperation from teams of ISS operations controllers, multiple engineering and design disciplines, management, and construction companies performing an array of activities simultaneously and in sync delivering a final product with no issues that impacted the schedule. For each console operator discipline, studies of Information Technology (IT) tools and equipment layouts, ergonomics, and lines of sight were performed. Infusing some of the latest IT into the project was an essential goal in ensuring future growth and success of the ISS payload science returns. Engineering evaluations led to a state of the art Video Wall implementation and more efficient ethernet cabling distribution providing the latest products and the best solution for the POIC. These engineering innovations led to cost savings for the project. Constraints involved in the management of the project included executing over 450 crew-hours of ISS real-time payload operations including a major onboard communications upgrade, SpaceX un-berth, a Soyuz launch, roll-out of ISS live video and interviews from the POIC, annual BCC certification and hurricane season, and ISS simulations and testing. Continuous ISS payload operations were possible during the PCA facility modifications with the reconfiguration of four control rooms and standup of two temporary control areas. Another major restriction to the project was an ongoing facility upgrade that included a NASA Headquarters mandated replacement of all electrical and mechanical systems and replacement of an external generator. These upgrades required a facility power outage during the PCA upgrades. The project also encompassed console layout designs and ordering, amenities selections and ordering, excessing of old equipment, moves, disposal of old IT equipment, camera installations, facility tour re-schedules, and contract justifications. These were just some of the tasks needed for a successful project. This paper describes the logistics and lessons learned in upgrading a control center capability in the middle of complex real-time operations. Combining the efficiencies of controller interaction and new technology infusion were prime drivers for this upgrade to handle the increased utilization of science research on ISS. The success of this project could not jeopardize the current operations while these facility upgrades occurred.

Dudley, Stephanie R. B.↗
NASA NTRS2014

Adaptive Controller Effects on Pilot Behavior

Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

Trujillo, Anna C.↗
NASA NTRS2015

Systems and Methods for Derivative-Free Adaptive Control

An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

Yucelen, Tansel↗
NASA NTRS2015

Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control

Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.

Kim, Kilsoo↗
NASA NTRS2016

Self-Guided Multimedia Stress Management and Resilience Training for Flight Controllers

Stress and anxiety-related problems are among the most common and costly behavioral health problems in society, and for those working in operational environments (i.e. astronauts, flight controllers, military) this can seriously impact crew performance, safety, and wellbeing. Technology-based interventions are effective for treating behavioral health problems, and can significantly improve the delivery of evidence-based health care. This study is evaluating the effectiveness, usefulness, and usability of a self-guided multimedia stress management and resilience training program in a randomized controlled trial (RCT) with a sample of flight controllers at Johnson Space Center. The intervention, SMART-OP (Stress Management and Resilience Training for Optimal Performance), is a six-session, cognitive behavioral-based computer program that uses self-guided, interactive activities to teach skills that can help individuals build resilience and manage stress. In a prior RCT with a sample of stressed but otherwise healthy individuals, SMART-OP reduced perceived stress and increased perceived control over stress in comparison to an Attention Control (AC) group. SMART-OP was rated as "highly useful" and "excellent" in usability and acceptability. Based on α-amylase data, individuals in SMART-OP recovered quicker and more completely from a social stress test as compared to the AC group [1]. In the current study, flight controllers are randomized either to receive SMART-OP training, or to a 6-week waitlist control period (WLC) before beginning SMART-OP. Eligible participants include JSC flight controllers and instructors without any medical or psychiatric disorder, but who are stressed based on self-report. Flight controllers provide a valid analog sample to astronauts in that they work in an operational setting, use similar terminology to astronauts, are mission-focused, and work under the same broader work culture. The study began in December 2014, and to date 79 flight controllers and instructors have expressed interest in the study, 49 of those were cleared for participation, we have screened 44 for eligibility, and 23 have met inclusion criteria. Recruitment is ongoing and the study will continue until December 2016. Outcome measures include perceived stress, perceived control over stress, resilience, mood, personality, emotion regulation, sleep, health behaviors, and psychophysiological data such as 24-hour heart rate, alpha amylase, and urinary and salivary cortisol. We are also collecting user feedback such as usability, working alliance, usefulness, and treatment credibility.

Rose, R. D.↗
NASA NTRS2018

Pterodactyl: Integrated Control Design for Precision Targeting of Deployable Entry Vehicles

Deployable Entry Vehicles (DEVs) enable in-situ scientific exploration at destinations with atmospheres across the solar system. Because they stow in a compact form and deploy only when ready to enter the atmosphere, DEVs relax the volume constraint imposed by rigid aeroshells. This work seeks to do for a DEV what the Wright Brothers did to propel modern day aviation: develop the guidance and control (G&C) methods that will make maneuvering and precision landing of DEV a reality. The Pterodactyl project objective is to deliver an integrated G&C methodology for a DEV, based on a detailed analysis that utilizes a Multi-disciplinary, Design, Analysis and Optimization (MDAO) framework. The current state-of-the-art for blunt body entry, G&C is rooted in the precision landing of vehicles such as Mars Science Laboratory (MSL) and Apollo, which used a propulsive reaction control system (RCS) to steer. Recent research has taken a particular interest in non-propulsive control for DEVs, including direct force control (angle of attack modulation via control surfaces or mass movement) and drag modulation (discrete change in ballistic coefficient). Using the MDAO framework that includes a guidance and control model to explore multiple control concepts for a DEV will shed light on the best design approach for these vehicles. In Pterodactyl, we will complete this study for a novel DEV concept, and then we will fabricate a functional prototype to help validate the design. The project is expected to down-select to a final control architecture by the end of 2018, and complete fabrication of the prototype by the end of 2019.The DEV chosen for detailed study in this project is the Adaptable Deployable Entry and Placement Technology (ADEPT). ADEPT uses a revolutionary 3D-woven carbon fabric that is foldable, can serve as primary structure, and can survive the extreme heating environment of atmospheric entry. The specific configuration of ADEPT under investigation is called Lifting Nano-ADEPT (LNA). LNA is designed for secondary payloads missions that require precision landing either for scientific objectives at a target destination or for payload recovery at Earth.The MDAO framework being created through this research, called COBRA-Pt (Composite Beam Roll-Up Solar Array-Prototype), will combine three critical elements of the system design: a guidance algorithm with Monte Carlo, a parametric control model, and vehicle geometry details. Novel control models being studied are deployable aerodynamic surfaces as well as shape morphing. These concepts will be compared at the system level with a more traditional propulsive RCS by comparing several key performance parameters. Upon completion of the design study, a functional prototype of LNA will be fabricated that will include the integration of guidance software and relevant control actuators. We expect this study will provide critical data that could feed into the development of an Earth-based flight test of LNA. The COBRA-Pt framework will provide a modular system by which to study any DEV concept in any atmosphere.

Smith, Brandon↗
NASA NTRS2019

Adaptive Control Law for PID

This paper is the final report for my Spring 2019 internship at the Kennedy Space Center in Cape Canaveral, Florida. The official title of my internship is 'Launch Vehicle Control Study internship,' and I spent the spring working in GMRO- Granular Mechanics and Regolith Operations. There are two components to my project involving developing an adaptive control law for a PID controller. The first component involves performing a deep study and analysis of adaptive control laws, with the goal of developing stability proofs about the control law and the gain and phase margins. The second component involves analyzing the data received after implementing the adaptive control law. Unfortunately, as of the time of writing this paper, the data is not considered ‘clean' enough to analyze. Therefore, in this paper I will give an overview of adaptive control law stability proofs and will write about the data analysis separately. Section II includes several general definitions, and the later sections have additional definitions at the end of each section.A PID (proportional integral derivative) controller is a common control algorithm which isimplemented in NASA’s rocket launch system. The idea behind the PID controller is to calculatethe error (current position – desired position) and drive it to zero by using proportional, integral,and derivative influences on the controller. For example, when a sailor steers a ship which isheading towards location 𝑥 but would like to turn the ship to reach location 𝑥∗, he/she wouldinitially turn the wheel significantly, and as the ship proceeds towards 𝑥∗ the sailor would slowlyshift the wheel back to its original position, and thereby drive the error, 𝑥∗ − 𝑥, to zero.

Eisenberg, Yael↗
NASA NTRS2020

Control Force Compensation in Ground-Based Flight Simulators

This paper presents the results of a study that investigated if controller force compensations accounting for the inertial force and moment due to the aircraft motion during flight have a significant effect on pilot control behavior and performance. Seven rotorcraft pilots performed a side-step and precision hovering task in light turbulence in the Vertical Motion Simulator. The effects of force compensation were examined for two different simulated rotorcraft: linear and UH-60 dynamics with two different force gradient of the lateral stick control. Four motion configurations were used: large motion, hexapod motion, fixed-base motion, and fixed-base motion with compensation. Control-input variables and task performance such as the time to translate to the designated hover position, station-keeping position errors, and handling qualities ratings were used as measures. Control force compensation enabled pilot control behavior and performance more similar to that under high- or medium-fidelity motion to some extent only. Control force compensation did not improve overall task performance considering both rotorcraft models at the same time. The control force compensation had effects on the linear model with lighter force gradient, but only a minimal effect on pilots? control behavior and task performance for the UH-60 model, which had a higher force gradient. This suggests that the control force compensation has limited benefits for controllers that have higher stiffness.

Chung, William W.↗
NASA NTRS2020

Control Force Compensation in Ground-Based Flight Simulators

This paper presents the results of a study that investigated if controller force compensations accounting for the inertial force and moment due to the aircraft motion during flight have a significant effect on pilot control behavior and performance. Seven rotorcraft pilots performed a side-step and precision hovering task in light turbulence in the Vertical Motion Simulator. The effects of force compensation were examined for two different simulated rotorcraft: linear and UH-60 dynamics with two different force gradient of the lateral stick control. Four motion configurations were used: large motion, hexapod motion, fixed-base motion, and fixed-base motion with compensation. Control-input variables and task performance such as the time to translate to the designated hover position, station-keeping position errors, and handling qualities ratings were used as measures. Control force compensation enabled pilot control behavior and performance more similar to that under high- or medium-fidelity motion to some extent only. Control force compensation did not improve overall task performance considering both rotorcraft models at the same time. The control force compensation had effects on the linear model with lighter force gradient, but only a minimal effect on pilots? control behavior and task performance for the UH-60 model, which had a higher force gradient. This suggests that the control force compensation has limited benefits for controllers that have higher stiffness.

Chung, William↗
NASA NTRS2024

Control Effectiveness: Metric Development and Application to Resilient Lunar Habitat Design

System safety engineering in its bare essence involves identifying, assessing, and mitigating, or controlling, hazards. Appropriate safety controls are selected using hazard reduction precedence principles, prior experience, or by assessing their impact on residual risk (together with other factors like cost). We propose a control effectiveness metric as one way to systematically and consistently evaluate potential safety controls individually and thereby facilitate selecting a shortlist of potential controls for subsequent integrated evaluation. The control effectiveness metric considers a safety control’s availability when needed, the probability that its design is adequate in addressing the targeted hazard, the probability that the design will be implemented as intended, and the relationship between the time it takes for the safety control to address its target hazard and the time before the hazard propagates. We demonstrated the use of our metric on a lunar habitat design using a physics-based habitat simulator. High control effectiveness and safety controls result in a habitat with high resilience, while low control effectiveness results in lower resilience.

Rashi Jain↗