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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Motion control of 7-DOF arms - The configuration control approach

Graphics simulation and real-time implementation of configuration control schemes for a redundant 7-DOF Robotics Research arm are described. The arm kinematics and motion control schemes are described briefly. This is followed by a description of a graphics simulation environment for 7-DOF arm control on the Silicon Graphics IRIS Workstation. Computer simulation results are presented to demonstrate elbow control, collision avoidance, and optimal joint movement as redundancy resolution goals. The laboratory setup for experimental validation of motion control of the 7-DOF Robotics Research arm is then described. The configuration control approach is implemented on a Motorola-68020/VME-bus-based real-time controller, with elbow positioning for redundancy resolution. Experimental results demonstrate the efficacy of configuration control for real-time control.

Seraji, Homayoun↗
NASA NTRS1995

A Comparison of Multivariable Control Design Techniques for a Turbofan Engine Control

This paper compares two previously published design procedures for two different multivariable control design techniques for application to a linear engine model of a jet engine. The two multivariable control design techniques compared were the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the H-Infinity synthesis. The two control design techniques were used with specific previously published design procedures to synthesize controls which would provide equivalent closed loop frequency response for the primary control loops while assuring adequate loop decoupling. The resulting controllers were then reduced in order to minimize the programming and data storage requirements for a typical implementation. The reduced order linear controllers designed by each method were combined with the linear model of an advanced turbofan engine and the system performance was evaluated for the continuous linear system. Included in the performance analysis are the resulting frequency and transient responses as well as actuator usage and rate capability for each design method. The controls were also analyzed for robustness with respect to structured uncertainties in the unmodeled system dynamics. The two controls were then compared for performance capability and hardware implementation issues.

Garg, Sanjay↗
NASA NTRS1997

Nonlinear Performance Seeking Control using Fuzzy Model Reference Learning Control and the Method of Steepest Descent

Performance Seeking Control (PSC) attempts to find and control the process at the operating condition that will generate maximum performance. In this paper a nonlinear multivariable PSC methodology will be developed, utilizing the Fuzzy Model Reference Learning Control (FMRLC) and the method of Steepest Descent or Gradient (SDG). This PSC control methodology employs the SDG method to find the operating condition that will generate maximum performance. This operating condition is in turn passed to the FMRLC controller as a set point for the control of the process. The conventional SDG algorithm is modified in this paper in order for convergence to occur monotonically. For the FMRLC control, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for effective tuning of the FMRLC controller.

Kopasakis, George↗
NASA NTRS1997

Universal Approximation of Mamdani Fuzzy Controllers and Fuzzy Logical Controllers

In this paper, we first distinguish two types of fuzzy controllers, Mamdani fuzzy controllers and fuzzy logical controllers. Mamdani fuzzy controllers are based on the idea of interpolation while fuzzy logical controllers are based on fuzzy logic in its narrow sense, i.e., fuzzy propositional logic. The two types of fuzzy controllers treat IF-THEN rules differently. In Mamdani fuzzy controllers, rules are treated disjunctively. In fuzzy logic controllers, rules are treated conjunctively. Finally, we provide a unified proof of the property of universal approximation for both types of fuzzy controllers.

Yuan, Bo↗
NASA NTRS2004

Chapter 9: MEMS Applications in Spacecraft Thermal Control and Chapter 13: Handling and Contamination Control Considerations for Critical Space Applications

Thermal control systems (TCS) are an integral part of all spacecraft and instruments. To operate properly all spacecraft components must be maintained within a specified temperature band, which in some instances can be quite tight (less than 1 degree C). Traditionally this is accomplished by "passive" designs, but with modem spacecraft and instruments it is increasingly necessary to use active thermal control technologies. Microelectromechanical System (MEMS) can be useful in developing an active TCS, and may be especially useful for small spacecraft. As the MEMS knowledge matures, the applications of MEMS in spacecraft thermal control emerges as a viable technology for thermal engineers. Potential applications include specialized thermal control coatings, thermal switches, and specialized filters for instruments. Although MEMS technology demonstrates benefits, it also poses challenges for thermal en,oineers due to the lack of in-flight MEMS data. As a consequence, in order to design a MEMS thermal control device and receive the full advantage, it is important to understand the potential impact of the space environment on MEMS devices and the design/operational constraints imposed in their use. An entire chapter is devoted to handling and contamination controls for Micro Electro Mechanical Systems (MEMS) in space applications due to the importance of the topic area to final mission success. Handling and contamination control is discussed relative to the full life cycle from the very basic wafer level processing up through on orbit deployment. MEMS packaging will drive the need to tailor the Handling and Contamination Control Plan in order to assure adequacy of the overall program on a program by program basis. Plan elements are discussed at length to assist the user in preparing and implementing effective plans for both handling and contamination control to prevent deleterious effects.

Osiander, Robert↗
NASA NTRS2007

Control of Dual-Opposed Stirling Convertors with Active Power Factor Correction Controllers

When using recently-developed active power factor correction (APFC) controllers in power systems comprised of dual-opposed free-piston Stirling convertors, a variety of configurations of the convertors and controller(s) can be considered, with configuration ultimately selected based on benefits of efficiency, reliability, and robust operation. The configuration must not only achieve stable control of the two convertors, but also synchronize and regulate motion of the pistons to minimize net dynamic forces. The NASA Glenn Research Center (GRC) System Dynamic Model (SDM) was used to study ten configurations of dual-opposed convertor systems. These configurations considered one controller with the alternators connected in series or in parallel, and two controllers with the alternators not connected (isolated). For the configurations where the alternators were not connected, several different approaches were evaluated to synchronize the two convertors. In addition, two thermodynamic configurations were considered: two convertors with isolated working spaces and convertors with a shared expansion space. Of the ten configurations studied, stable operating modes were found for four. Three of those four had a common expansion space. One stable configuration was found for the dual-opposed convertors with separate working spaces. That configuration required isochronous control of both convertors, and two APFC controllers were used to accomplish this. A frequency/phase control loop was necessary to allow each APFC controller to synchronize its associated convertor with a common frequency.

Regan, Timothy F.↗
NASA NTRS2010

Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

Burken, John J.↗
NASA NTRS2006

Control of Dual-Opposed Stirling Convertors with Active Power Factor Correction Controllers

When using recently-developed active power factor correction (APFC) controllers in power systems comprised of dual-opposed free-piston Stirling convertors, a variety of configurations of the convertors and controller(s) can be considered, with configuration ultimately selected based on benefits of efficiency, reliability, and robust operation. The configuration must not only achieve stable control of the two convertors, but also synchronize and regulate motion of the pistons to minimize net dynamic forces. The NASA Glenn Research Center (GRC) System Dynamic Model (SDM) was used to study ten configurations of dual-opposed convertor systems. These configurations considered one controller with the alternators connected in series or in parallel, and two controllers with the alternators not connected (isolated). For the configurations where the alternators were not connected, several different approaches were evaluated to synchronize the two convertors. In addition, two thermodynamic configurations were considered: two convertors with isolated working spaces and convertors with a shared expansion space. Of the ten configurations studied, stable operating modes were found for four. Three of those four had a common expansion space. One stable configuration was found for the dual-opposed convertors with separate working spaces. That configuration required isochronous control of both convertors, and two APFC controllers were used to accomplish this. A frequency/phase control loop was necessary to allow each APFC controller to synchronize its associated convertor with a common frequency.

Regan, Timothy F.↗
NASA NTRS2010

Success Stories in Control: Nonlinear Dynamic Inversion Control

NASA plays an important role in advancing the state of the art in flight control systems. In the case of Nonlinear Dynamic Inversion (NDI) NASA supported initial implementation of the theory in an aircraft and demonstration in a space vehicle. Dr. Dale Enns of Honeywell Aerospace Advanced Technology performed this work in cooperation with NASA and under NASA contract. Honeywell and Lockheed Martin were subsequently contracted by AFRL to create "Design Guidelines for Multivariable Control Theory". This foundational work directly contributed to the advancement of the technology and the credibility of the control law as a design option. As a result Honeywell collaborated with Lockheed Martin to produce a Nonlinear Dynamic Inversion controller for the X-35 and subsequently Lockheed Martin did the same for the production Lockheed Martin F-35 vehicle. The theory behind NDI is to use a systematic generalized approach to controlling a vehicle. Using general aircraft nonlinear equations of motion and onboard aerodynamic, mass properties, and engine models specific to the vehicle, a relationship between control effectors and desired aircraft motion can be formulated. Using this formulation a control combination is used that provides a predictable response to commanded motion. Control loops around this formulation shape the response as desired and provide robustness to modeling errors. Once the control law is designed it can be used on a similar class of vehicle with only an update to the vehicle specific onboard models.

Bosworth, John T.↗
NASA NTRS2011

Automated Air Traffic Control Operations with Weather and Time-Constraints: A First Look at (Simulated) Far-Term Control Room Operations

In this paper we discuss results from a recent high fidelity simulation of air traffic control operations with automated separation assurance in the presence of weather and time-constraints. We report findings from a human-in-the-loop study conducted in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. During four afternoons in early 2010, fifteen active and recently retired air traffic controllers and supervisors controlled high levels of traffic in a highly automated environment during three-hour long scenarios, For each scenario, twelve air traffic controllers operated eight sector positions in two air traffic control areas and were supervised by three front line managers, Controllers worked one-hour shifts, were relieved by other controllers, took a 3D-minute break, and worked another one-hour shift. On average, twice today's traffic density was simulated with more than 2200 aircraft per traffic scenario. The scenarios were designed to create peaks and valleys in traffic density, growing and decaying convective weather areas, and expose controllers to heavy and light metering conditions. This design enabled an initial look at a broad spectrum of workload, challenge, boredom, and fatigue in an otherwise uncharted territory of future operations. In this paper we report human/system integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. We conclude that, with further refinements. air traffic control operations with ground-based automated separation assurance can be an effective and acceptable means to routinely provide very high traffic throughput in the en route airspace.

Prevot, Thomas↗
NASA NTRS2004

Improving Control of Two Motor Controllers

A computer program controls motors that drive translation stages in a metrology system that consists of a pair of two-axis cathetometers. This program is specific to Compumotor Gemini (or equivalent) motors and the Compumotor 6K-series (or equivalent) motor controller. Relative to the software supplied with the controller, this program affords more capabilities and is easier to use. Written as a Virtual Instrument in the LabVIEW software system, the program presents an imitation control panel that the user can manipulate by use of a keyboard and mouse. There are three modes of operation: command, movement, and joystick. In command mode, single commands are sent to the controller for troubleshooting. In movement mode, distance, speed, and/or acceleration commands are sent to the controller. Position readouts from the motors and from position encoders on the translation stages are displayed in marked fields. At any time, the position readouts can be recorded in a file named by the user. In joystick mode, the program yields control of the motors to a joystick. The program sends commands to, and receives data from, the controller via a serial cable connection, using the serial-communication portion of the software supplied with the controller.

Toland, Ronald W.↗
NASA NTRS2012

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Nguyen, Nhan T.↗
NASA NTRS2013

Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.

Abdallah, Muhammad E.↗
DOE OSTI2023

How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system

Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic programming problem, and these two have shown significant operational cost saving potentials for building energy systems. Furthermore, there is still a lack of in-depth quantitative studies on their approximation levels to the true optimality, especially in the building energy domain. To fill in the gap, this paper provides a numerical framework that enables the evaluation of the optimality levels of different controllers for building energy systems. This framework is then used to comprehensively compare the optimal control performance of both MPC and DRL controllers with given computation budgets for a single zone fan coil unit system. Note the optimality is estimated based on a user-specific selection of trade-off weights among energy costs, thermal comfort and control slew rates. Compared with the best optimality we can find through expensive optimization simulations, the best DRL agent can maximally approximate the optimality by 96.54%, which outperforms the best MPC whose optimality level is 90.11%. However, due to the stochasticity, the DRL agent is only expected to approximate the optimality by 90.42%, which is almost equivalent to the best MPC. Except for Proximal Policy Optimization (PPO), all DRL agents can have a better approximation to the optimality than the best MPC, and are expected to have better approximation than the MPC with a prediction horizon of 32 steps (15 min per step). In terms of reducing energy cost and thermal discomfort, MPC can outperform the rule-based control (RBC) by 18.47%–25.44%. DRL can be expected to outperform RBC by 18.95%–25.65% ,and the best DRL control policy can outperform RBC by 20.29%–29.72%. Although the comparison of the optimality level is performed in a perfect setting, e.g., MPC assumes perfect models, and DRL assumes a perfect offline training process and online deployment process, this can shed insight on their capabilities of approximating to the original dynamic programming problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Generic Primary-Control Model for Grid-Forming Inverters: Towards Interoperable Operation & Control

This paper outlines an architectural vision centered around the notion of interoperability to integrate grid-forming inverter-based resources in large-scale grids. With the underlying principle of interoperability guiding developments, we focus on modeling the characteristics of droop, virtual synchronous machine, and virtual oscillator controls. Emphasis is placed on these three controllers since they are leading grid-forming control candidates and are likely to be commonplace as primary-control schemes in future systems. We show that these controllers can each be considered as instantiations of a more generic model and that all these controllers exhibit similar droop-like relations between pertinent terminal variables in steady state. This commonality between controllers gives interoperability among them such that automatic synchronization, power sharing, and voltage regulation can be achieved. Simulation results validate the models and demonstrate how the steady-state droop characteristics of these control methods can be aligned with the aid of the developed modeling paradigm.

control↗
DOE OSTI2024

On the evaluation and selection of network-level traffic control policies: Perimeter control, TUC, and their combination

Perimeter control (PC) of urban traffic networks can be effective in increasing network-wide efficiency. PC operates on the border of a protected region of a traffic network. Most studies thus far considered fixed-time plans for the inner part of these regions. A few studies have shown that combining PC with locally actuated or decentralized traffic control systems may have positive effects on traffic performance, including better-defined Network Macroscopic Fundamental Diagrams (NMFDs), increased network throughput, and reduced delays. The Traffic-responsive Urban Control (TUC) is a real-time network-wide traffic control system with particular design characteristics, such as the balancing of link's occupancies and an inherent gating feature. These characteristics suggest that TUC may enhance the traffic network performance when combined with PC whilst improving the resulting NMFDs and network throughput and delays. Here, in this work, we investigate the effect of feedback perimeter control (FPC), TUC, and their combination on the NMFD and on the traffic conditions of general traffic and public transport in the microsimulation of a realistic model of the Christchurch Central Business District in New Zealand. We perform a thorough investigation of practical aspects of both control strategies and their combination, including parameter tuning and infrastructure requirements, and how they may affect the control system choice. Results show higher throughput and less hysteresis on the NMFDs, particularly when TUC is involved. PC provides benefits concentrated in the protected region which can greatly benefit public transportation if there is an overlap with the transit network. The combination of TUC and FPC boosts network-wide throughput.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Comparative Analysis of Model Predictive Control and MPC-Informed Rule-Based Control for Thermal Storage Operation in Ultra-Low Temperature 4th Generation District Heating Networks

The integration of thermal storage and heat pumps in district heating networks (DHNs) can significantly enhance operational flexibility and energy efficiency; however, the practical deployment of advanced control strategies is often hindered by forecasting requirements and computational complexity. This study presents a comparative analysis of thermal storage control strategies in an ultra-low-temperature fourth-generation DHN, focusing on the development of a simplified rule-based control (RBC) explicitly informed by Model Predictive Control (MPC) behavior. The proposed methodology systematically analyzes the charging and discharging decisions of an MPC-controlled system under ideal forecasting conditions and extracts recurrent control patterns as a function of key system variables, including outdoor temperature, thermal demand, and electricity price. These patterns are translated into a set of structured time- and condition-based rules, resulting in an MPC-informed RBC that embeds predictive insights while preserving implementation simplicity and operational transparency. The approach is validated on a realistic mixed-use urban district in Denver, Colorado, USA, equipped with a centralized air-source heat pump, distributed water-to-water heat pumps, and a central thermal storage unit. Results show that the tuned RBC attains approximately 96% of ideal MPC economic performance (-27% of costs), preserves values of technical and environmental indicators (reduction only of 2-3%), and substantially reduces complexity. Sensitivity analyses further demonstrate the robustness of the RBC under varying operational conditions (i.e., ambient temperature, electricity price). Overall, the study demonstrates that MPC-informed rule-based control represents an effective trade-off between control performance and real-world applicability, enabling the integration of additional system components while maintaining simplicity, robustness, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A microchip microcontroller-based transducer controller for non-contact scanning probe microscopy with phase-locked loop, amplitude, and Q control

An inexpensive yet versatile transducer controller for non-contact scanning probe microscopy (SPM) based on a PIC32 microcontroller from Microchip Technology, Inc is described. In addition to feedback control using the amplitude or phase of the signal from the non-contact transducer, the controller includes a phase-locked loop for frequency-shift feedback, as well as fixed-amplitude, quality factor (Q) control, and self-excitation modes. Apart from the input amplifiers, output buffers, and the Q-control circuit, all other functions of the controller are instantiated in software on the microchip, enabling rapid changes in operating parameters if needed. The controller communicates with a host personal computer via a simple serial connection. The controller has been tested with a quartz tuning-fork transducer but can be used with any oscillating non-contact transducer.

47 OTHER INSTRUMENTATION↗