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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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Proportional control circuit supplies a heater with full current, from a pulsating dc source, to a present temperature and then switches to proportional control for fine temperature regulation. Two resistors and a diode are added to the existing circuit. The circuit can be adapted to control other functions.
Proportional controller for regulating aircraft or spacecraft motion about three axes
Proportional controller for motor speed provides full 0- to 100-percent linear control of durations of motor-driving pulses. Controller uses commercially available LM3900 integrated circuit, which requires only single supply voltage of 4 to 30 V. Control voltage provided by adjustable potentiometer or by external source of feedback information such as motor-speed sensing circuit.
A self-regulating proportionally controlled heating apparatus and technique is provided wherein a single electrical resistance heating element having a temperature coefficient of resistance serves simultaneously as a heater and temperature sensor. The heating element is current-driven and the voltage drop across the heating element is monitored and a component extracted which is attributable to a change in actual temperature of the heating element from a desired reference temperature, so as to produce a resulting error signal. The error signal is utilized to control the level of the heater drive current and the actual heater temperature in a direction to reduce the noted temperature difference. The continuous nature of the process for deriving the error signal feedback information results in true proportional control of the heating element without the necessity for current-switching which may interfere with nearby sensitive circuits, and with no cyclical variation in the controlled temperature.
Multi-channel proportional control system for operation of dc motors for use with externally-powered orthotic arm braces is described. Components of circuitry and principles of operation are described. Schematic diagram of control circuit is provided.
In this study, the control of a desiccant-wheel-based evaporative cooling system with a double-layer dew-point cooler system is emphasized. There are two dew-point evaporative coolers in the system and the air taken inside is subjected to pre- and post-cooling processes. The dehumidification process of the air taken in is carried out by the desiccant wheel after the pre-cooling process. A proportional-based control strategy has been developed to adjust the temperature and relative humidity of the room quickly and robustly with different operation modes for actuators to bring comfort with less energy consumption. In addition, an automatic Stop/Run mode has been added to the control strategy to save extra energy. With the developed control strategy, enabling the actuators to switch between the operation modes, more energy savings are achieved compared to both traditional ON/OFF and proportional controls. The accuracy and applicability of the developed control strategy were analyzed and it was observed that the room comfort reached the desired levels successfully under all disruptive effects. The control inputs and the energies consumed by all the actuators were investigated and it was determined that 21.19% more energy savings are provided by adding the automatic Stop/Run feature. With the multi-mode control strategy, a total of 40.90% less energy consumption is achieved compared to the classical ON/OFF control technique. Thus, it is seen that the controller developed for the desiccant-wheel-based evaporative cooler is a viable method to provide fast and robust comfort conditions with less energy.
Inspection and testing of proportional temperature controller for air conditioning system of Saturn IB launch vehicle
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Through theoretical and analog results the effects of two nonlinear stability derivatives on the longitudinal motions of an aircraft have been investigated. Nonlinear functions of pitching-moment and lift coefficients with angle of attack were considered. Analog results of aircraft motions in response to step elevator deflections and to the action of the proportional control systems are presented. The occurrence of continuous hunting oscillations was predicted and demonstrated for the attitude stabilization system with proportional control for certain nonlinear pitching-moment variations and autopilot adjustments.
Providing room comfort quickly by using less energy in cooling systems is important both in terms of efficiency and environment. In this study, independent temperature/humidity control strategies are designed for precooled desiccant based evaporative cooling system to provide room comfort quickly with less energy. Therefore, the speed controls of the system's actuators become important depending on the room, cooler and atmosphere conditions. The mathematical models are obtained to determine the relation between voltages of actuators and the variations in the room's temperature and humidity. After that, new control strategies are developed based on Proportional and Fuzzy+Proportional techniques and the control performance is increased by adding extra modes to the operation of the actuators. The effects of the control techniques on the cooling performance and energy consumption were investigated for different cases. It has been observed that the room temperature and relative humidity reach the set values in a short time for both techniques and are successfully kept at these values under the disturbances. By using Fuzzy+Proportional controller, the robustness of the cooler increases due to more precisely adjustment of controller's parameter depending the system conditions. Finally, both control strategies provide more than 20% energy savings compared to the traditional ON/OFF control.
This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.
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The following poster presents a couple of approaches for temperature control at heat exchanger’s exit. One of the approaches is based on using n-step ahead neural network while the other approach utilizes a combination of control + learning module for temperature control. Designing robust controllers for typical heat exchangers is very challenging primarily because of complexities associated with the synthesis of dynamics of industrial heat exchangers. Even if a dynamics model is synthesized, the accuracy of it would be called into question as there can be lot of unmodeled system dynamics and random noise in input parameters. In many situations, the degree of uncertainty in the model of system being controlled limits the utility of optimal control design. Controller can be manually tuned on the field but it is very difficult to determine manual adjustments that result in overall improvement. These practical challenges call for learning based approaches for temperature control that would result in optimal heat exchanger performance. We utilize the existing mathematical model for air-water system synthesized by Underwood and Crawford for testing our algorithms. Underwood and Crawford developed a model of heating coil by fitting a second-order non-linear equations to measurements of air and water temperature and flow rates obtained from the actual coil. The uncertainties in the model include air and water inlet temperatures and air-flow rate. These uncertainties are modeled as random variables that are sampled from a uniform distribution. The control variable is the water flow rate which is controlled for regulating the air-outlet temperature. Neural networks are frequently used in various literatures for learning time-series. We propose a modified version of neural networks known as n-step ahead neural network that take the state variables and output at time t as input to successfully predict output at time t+n. The variable n is a hyper-parameter which can be optimized based on performance constraints. The n-step ahead neural network was then trained on training data generated from experimental model to high training accuracies. This trained model performed appreciably in its objective to regulate outlet temperature of a heat exchanger. The second approach uses a combination of control and learning module for temperature regulation. The control module used is a proportional controller while the learning module used is steady state neural network. The steady state neural network is used to learn the controller output as a function of random variables and temperature set-point. The proportional controller is then used to compensate for transient behavior of linearized system around various operating points. The algorithm works effectively for temperature regulation as neural network captures the non-linear input-output behavior of closed loop system leaving proportional controller to compensate for steady state errors of a linearized plant. The proposed algorithm’s performances were evaluated against the performance of a PI controller. Further, the robustness of the algorithms were also studied in great detail under small perturbations around tuned parameters of the proposed algorithms.
Wake effects cause wind turbine generators (WTGs) within a wind power plant (WPP) to produce different levels of active power and subsequent reactive power capabilities. Further, the impedance between a WTG and the point of interconnection (POI)-which depends on the distance between them-impacts the WPP's reactive power injection capability at the POI. This paper proposes a voltage control scheme for a WPP based on the available reactive current of the doubly-fed induction generators (DFIGs) and its impacts on the POI to improve the reactive power injection capability of the WPP. In this paper, a design strategy for modifying the gain of DFIG controller is suggested and the comprehensive properties of these control gains are investigated. In the proposed scheme, the WPP controller, which operates in a voltage control mode, sends the command signal to the DFIGs based on the voltage difference at the POI. The DFIG controllers, which operate in a voltage control mode, employ a proportional controller with a limiter. The gain of the proportional controller is adjusted depending on the available reactive current of the DFIG and the series impedance between the DFIG and the POI. The performance of the proposed scheme is validated for various disturbances such as a reactive load connection and grid fault using an EMTP-RV simulator. Furthermore, simulation results demonstrate that the proposed scheme promptly recovers the POI voltage by injecting more reactive power after a disturbance than the conventional scheme.
Temperature control of radiation sensors, targets, and other critical components is a common requirement in modern scientific instruments. Conventional control systems use a heater and a temperature sensor mounted on the body to be controlled. For proportional control, the sensor provides feedback to circuitry which drives the heater with an amount of power proportional to the temperature error. It is impractical or undesirable to mount both a heater and a sensor on certain components such as ultra-small parts or thin filaments. In principle, a variable current through the element is used for heating, and the change in voltage drop due to the element's temperature coefficient is separated and used to monitor or control its own temperature. Since there are no thermal propagation delays between heater and sensor, such control systems are exceptionally stable.
Proportional-integral-derivative (PID) controllers in water resource recovery facilities (WRRFs) feedback control loops are commonplace. While simple to implement, such control loops are rarely tuned optimally or systematically. Heuristic tuning approaches are commonly applied with varying degrees of success using trial-and-error, ad hoc tuning rules, or duplication of tuning values from a similar system. However, there are effective methods, such as lambda tuning, produce acceptable tuning with limited effort. These are based on the step-response method, where a manual process perturbation is used to define the relationship between the manipulated and controlled variables. Based on such an experiment, a simple process model is constructed and used to determine the controller tuning values. In this work, we used the step-response method and lambda tuning for two control systems in full-scale WRRFs. This led to responsive and stable behavior of the controlled system as defined by the absolute average error of the controlled variable to setpoint and standard deviation of the manipulated variable. Tuning of feedback control loops can be completed successfully through a systematic approach, and this work suggests that tuning tools, like lambda, should be part of all wastewater treatment control engineers' toolbox.
The powered hook with trigger finger appears to be a useful adaptation of a terminal device for an amputee when performing vocational activities involving the use of a powered tool requiring a trigger control. The proportional control system includes transducers and amplifiers and appears to have widespread application for control of any external power, whether it be in the orthotic or prosthetic field.
As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.