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At least 19 records

Contact position sensor using constant contact force control system

A force control system (50) and method are provided for controlling a position contact sensor (10) so as to produce a constant controlled contact force therewith. The system (50) includes a contact position sensor (10) which has a contact probe (12) for contacting the surface of a target to be measured and an output signal (V.sub.o) for providing a position indication thereof. An actuator (30) is provided for controllably driving the contact position sensor (10) in response to an actuation control signal (I). A controller (52) receives the position indication signal (V.sub.o) and generates in response thereto the actuation control signal (I) so as to provide a substantially constant selective force (F) exerted by the contact probe (12). The actuation drive signal (I) is generated further in response to substantially linear approximation curves based on predetermined force and position data attained from the sensor (10) and the actuator (30).

Sturdevant, Jay↗

Traffic Signal Optimization by Integrating Reinforcement Learning and Digital Twins

Machine learning (ML) methods, especially reinforcement learning (RL), have been widely considered for traffic signal optimization in intelligent transportation systems. Most of these ML methods are centralized, lacking in scalability and adaptability in large traffic networks. Further, it is challenging to train such ML models due to the lack of training platforms and/or the cost of deploying and training in a real traffic networks. This paper presents an approach for the integration of decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin (DT) to optimize traffic signals for the reduction of traffic congestion and network-wide fuel consumption related to stopping. Specifically, the DGMARL agents learn traffic state patterns and make decisions regarding traffic signal control with assistance from a Digital Twin module, which simulates and replicates the traffic behaviors of a real traffic network. The proposed approach was evaluated using PTV-Vissim [1], a microscopic traffic simulation platform. PTV-Vissim is also the simulation engine of the DT, enabling emulation and optimization of the traffic signals on the MLK Smart Corridor in Chattanooga, Tennessee. Compared to an actuated signal control baseline approach, experiment results show that Eco_PI, a developed performance measure capturing the impact of stops on fuel consumption, was reduced by 44.27% in a 24-hour and an average of 29.88% in a PM-peak-hour scenario.

Multi-Agent Reinforcement Learning, Digital Twin, ↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗

Design of a powered elevator control system

The design, fabrication and flight testing of a powered elevator system for the Augmentor Wing Jet STOL Research Aircraft (AWJSRA or Mod C-8A) are discussed. The system replaces a manual spring tab elevator control system that was unsatisfactory in the STOL flight regime. Pitch control in the AWJSRA is by means of a single elevator control surface. The elevator is used for both maneuver and trim control as the stabilizer is fixed. A fully powered, irreversible flight control system powered by dual hydraulic sources was designed. The existing control columns and single mechanical cable system of the AWJSRA have been retained as has been the basic elevator surface, except that the elevator spring tab is modified into a geared balance tab. The control surface is directly actuated by a dual tandem moving body actuator. Control signals are transmitted from the elevator aft quadrant to the actuator by a linkage system that includes a limited authority series servo actuator.

Glende, W. L. B.↗

Adaptive Strategies for Controls of Flexible Arms

An adaptive controller for a modern manipulator has been designed based on asymptotical stability via the Lyapunov criterion with the output error between the system and a reference model used as the actuating control signal. Computer simulations were carried out to test the design. The combination of the adaptive controller and a system vibration and mode shape estimator show that the flexible arm should move along a pre-defined trajectory with high-speed motion and fast vibration setting time. An existing computer-controlled prototype two link manipulator, RALF (Robotic Arm, Large Flexible), with a parallel mechanism driven by hydraulic actuators was used to verify the mathematical analysis. The experimental results illustrate that assumed modes found from finite element techniques can be used to derive the equations of motion with acceptable accuracy. The robust adaptive (modal) control is implemented to compensate for unmodelled modes and nonlinearities and is compared with the joint feedback control in additional experiments. Preliminary results show promise for the experimental control algorithm.

Yuan, Bau-San↗

Blood monitoring systems and methods thereof

A blood monitoring system is capable of monitoring the blood of a subject in vivo. The blood monitoring system comprises: 1) an array of movable microneedle micromachined within associated wells; 2) array of motion actuators able to move each needle in and out of their associated wells; 3) array of microvalves associated with each microneedle able to control the flow of air around the microneedle; 4) an array of chemical sensors inserted into patient by movable microneedles; 5) an array of inductors able to measure chemical concentration in the vicinity of inserted chemical sensors; 6) conducting vias that provide timed actuating signal signals from a control system to each motion actuator; 7) conducting vias that transmit signal produced by array of chemical sensors to the control system for processing, although the blood monitoring system can comprise other numbers and types of elements in other configurations.

Mir, Jose↗

Traffic Signal Control With Adaptive Online-Learning Scheme Using Multiple-Model Neural Networks

This article proposes a new traffic signal control algorithm to deal with unknown-traffic-system uncertainties and reduce delays in vehicle travel time. Unknown-traffic-system dynamics are approximated using a recurrent neural network (NN). To accurately identify the traffic system model, an online-learning scheme is developed to switch among a set of candidate NNs (i.e., multiple-model NNs) based on their estimation errors. Then, a bank of optimal signal-timing controllers is designed based on the online identification of the traffic system. Simulation studies have been carried out for the obtained control strategies using multiple-model NNs, and the desired results have been obtained. Moreover, compared with the widely used actuated traffic signal control schemes, it is shown that the proposed method can reduce vehicle travel delays and improve traffic system robustness.

99 GENERAL AND MISCELLANEOUS↗

Combined Cycle Engine Large-Scale Inlet for Mode Transition Experiments: System Identification Rack Hardware Design

The System Identification (SysID) Rack is a real-time hardware-in-the-loop data acquisition (DAQ) and control instrument rack that was designed and built to support inlet testing in the NASA Glenn Research Center 10- by 10-Foot Supersonic Wind Tunnel. This instrument rack is used to support experiments on the Combined-Cycle Engine Large-Scale Inlet for Mode Transition Experiment (CCE‒ LIMX). The CCE‒LIMX is a testbed for an integrated dual flow-path inlet configuration with the two flow paths in an over-and-under arrangement such that the high-speed flow path is located below the lowspeed flow path. The CCE‒LIMX includes multiple actuators that are designed to redirect airflow from one flow path to the other; this action is referred to as "inlet mode transition." Multiple phases of experiments have been planned to support research that investigates inlet mode transition: inlet characterization (Phase-1) and system identification (Phase-2). The SysID Rack hardware design met the following requirements to support Phase-1 and Phase-2 experiments: safely and effectively move multiple actuators individually or synchronously; sample and save effector control and position sensor feedback signals; automate control of actuator positioning based on a mode transition schedule; sample and save pressure sensor signals; and perform DAQ and control processes operating at 2.5 KHz. This document describes the hardware components used to build the SysID Rack including their function, specifications, and system interface. Furthermore, provided in this document are a SysID Rack effectors signal list (signal flow); system identification experiment setup; illustrations indicating a typical SysID Rack experiment; and a SysID Rack performance overview for Phase-1 and Phase-2 experiments. The SysID Rack described in this document was a useful tool to meet the project objectives.

Thomas, Randy↗

Fiber optics for aircraft engine/inlet control

NASA programs that focus on the use of fiber optics for aircraft engine/inlet control are reviewed. Fiber optics for aircraft control is attractive because of its inherent immunity to EMI and RFI noise. Optical signals can be safely transmitted through areas that contain flammable or explosive materials. The use of optics also makes remote sensing feasible by eliminating the need for electrical wires to be connected between sensors and computers. Using low-level optical signals to control actuators is also feasible when power is generated at the actuator. Each application of fiber optics for aircraft control has different requirements for both the optical cables and the optical connectors. Sensors that measure position and speed by using slotted plates can use lossy cables and bundle connectors if data transfer is in the parallel mode. If position and speed signals are multiplexed, cable and connector requirements change. Other sensors that depend on changes in transmission through materials require dependable characteristics of both the optical cables and the optical connectors. A variety of sensor types are reviewed, including rotary position encoders, tachometers, temperature sensors, and blade tip clearance sensors for compressors and turbines. Research on a gallium arsenide photoswitch for optically switched actuators that operate at 250 C is also described.

Baumbick, R. J.↗

NEMA-Phase Compliant Traffic Signal Controller Module in SUMO

The controller modules in SUMO use a stage-based control structure. A phase is defined as a stage of all allowed movements at a time instance. However, traffic signal controllers used in North America widely use National Electrical Manufacturers Association (NEMA) phase definition. A NEMA phase is defined by a certain flow movement at an intersection. At one time, more than one NEMA phase could happen together as long as they do not conflict with each other. We can visualize the NEMA phases and timings in Ring-and-Barrier structured NEMA diagrams. For one controller, only one phase from a ring can be activated at a time. Phases from different rings could be activated together as long as they are not from the different sides of a barrier. When a controller is operated in fixed-time control mode, we can model the NEMA phase timing as a corresponding stage-based control timing without any issues. When introducing actuation into the signal control, a Ring-and-Barrier structured traffic signal controller can be more flexible than stage-based controller by allowing different possible phase combinations. We made two efforts in modeling Ring-and-Barrier structured controllers in SUMO. One is to translate a NEMA phases timing into SUMO-readable phases and timings as an additional file for SUMO. This translation worked well for fixed-time control. To model actuated control and coordinated actuated control, we augmented the SUMO source code by adding a Ring-and-Barrier structured controller module. This module could implement traffic signal timing from controllers using NEMA phases. We also augmented TraCI to be able to set new NEMA phase timings during simulations. We examined the Ring-and-Barrier structured traffic signal controller module by both visually observing the simulation animations and the simulation records. The developed control module can model the generalized Ring-and-Barrier structured traffic signal timing that is used in North America. SEE: https://github.com/eclipse/sumo/blob/main/src/microsim/traffic_lights/NEMAController.cpp

Wang, Qichao↗

Compensating Function for Antenna Pointing

Mean-square errors of antenna surface reduced. Compensating function helps point deformable antenna without inducing excessive pointing oscillations or deformations of reflecting surface. When implemented on computer in real time, function enables calculation of control signals in response to several sensor inputs: Function devised so signals control torque actuator of antenna-pointing mechanism in way to reduce or minimize squares of errors of antenna surface over long time.

Mingori, D. L.↗

Active control of fan noise from a turbofan engine

A three channel active control system is applied to an operational turbofan engine in order to reduce tonal noise produced by both the fan and high pressure compressor. The control approach is the feedforward filtered-x least-mean-square algorithm implemented on a digital signal processing board. Reference transducers mounted on the engine case provides blade passing and harmonics frequency information to the controller. Error information is provided by large area microphones placed in the acoustic far field. In order to minimize the error signal, the controller actuates loudspeakers mounted on the inlet to produce destructive interference. The sound pressure level of the fundamental tone of the fan was reduced using the three channel controller by up to 16 dB over a 60 deg angle about the engine axis. A single channel controller could produce reduction over a 30 deg angle. The experimental results show the control to be robust. Simultaneous control of two tones is done with parallel controllers. The fundamental and the first harmonic tones of the fan were controlled simultaneously with reductions of 12 dBA and 5 dBA, respectively, measured on the engine axis. Simultaneous control was also demonstrated for the fan fundamental and the high pressure compressor fundamental tones.

Thomas, Russell H.↗

Active control of fan noise from a turbofan engine

A three-channel active control system is applied to an operational turbofan engine to reduce tonal noise produced by both the fan and the high-pressure compressor. The control approach is the feedforward filtered-x least-mean-square algorithm implemented on a digital signal processing board. Reference transducers mounted on the engine case provide blade passing and harmonics frequency information to the controller. Error information is provided by large area microphones placed in the acoustic far field. To minimize the error signal, the controller actuates loudspeakers mounted on the inlet to produce destructive interference. The sound pressure level of the fundamental tone of the fan was reduced using the three-channel controller by up to 16 dB over a +/- 30-deg angle about the engine axis. A single-channel controller could produce reduction over a +/- 15-deg angle. The experimental results show the control to be robust. Outside of the areas contolled, the levels of the tone actually increased due to the generation of radial modes by the control sources. Simultaneous control of two tones is achieved with parallel controllers. The fundamental and the first harmonic tones of the fan were controlled simultaneously with reductions of 12 and 5 dBA, respectively, measured on the engine axis. Simultaneous control was also demonstrated for the fan fundamental and the high-pressure compressor fundamental tones.

Thomas, Russell H.↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

Method and apparatus for reducing spacecraft instrument induced jitter via multifrequency cancellation

A method, apparatus, article of manufacture, and a memory structure for compensating for instrument induced spacecraft jitter is disclosed. The apparatus comprises a spacecraft control processor for producing an actuator command signal, a signal generator, for producing a cancellation signal having at least one harmonic having a frequency and an amplitude substantially equal to that of a disturbance harmonic interacting with a spacecraft structural resonance and a phase substantially out of phase with the disturbance harmonic interacting with the spacecraft structural resonance, and at least one spacecraft control actuator, communicatively coupled to the spacecraft control processor and the signal generator for inducing satellite motion according to the actuator command signal and the cancellation signal. The method comprises the steps of generating a cancellation signal having at least one harmonic having a frequency and an amplitude substantially equal to that of a disturbance harmonic interacting with a spacecraft structural resonance and a phase substantially out of phase with the disturbance harmonic interacting with the spacecraft structural resonance, and providing the cancellation signal to a spacecraft control actuator. The apparatus comprises a storage device tangibly embodying the method steps described above.

Liu, Ketao↗

Piezoelectric devices for vibration suppression: Modeling and application to a truss structure

For a space structure assembled from truss members, an effective way to control the structure may be to replace the regular truss elements by active members. The active members play the role of load carrying elements as well as actuators. A piezo strut, made of a stack of piezoceramics, may be an ideal active member to be integrated into a truss space structure. An electrically driven piezo strut generates a pair of forces, and is considered as a two-point actuator in contrast to a one-point actuator such as a thruster or a shaker. To achieve good structural vibration control, sensing signals compatible to the control actuators are desirable. A strain gage or a piezo film with proper signal conditioning to measure member strain or strain rate, respectively, are ideal control sensors for use with a piezo actuator. The Phase 0 CSI Evolutionary Model (CEM) at NASA Langley Research Center used cold air thrusters as actuators to control both rigid body motions and flexible body vibrations. For the Phase 1 and 2 CEM, it is proposed to use piezo struts to control the flexible modes and thrusters to control the rigid body modes. A tenbay truss structure with active piezo struts is built to study the modeling, controller designs, and experimental issues. In this paper, the tenbay structure with piezo active members is modelled using an energy method approach. Decentralized and centralized control schemes are designed and implemented, and preliminary analytical and experimental results are presented.

Won, Chin C.↗