Search NASA⌕ Search

SEARCH · Search NASA

Results for “PID 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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Integration of an Autopilot for a Micro Air Vehicle

Two autopilots providing autonomous flight capabilities are presented herein. The first is the Pico-Pilot, demonstrated for the 12-inch size class of micro air vehicles. The second is the MicroPilot MP2028(sup g), where its integration into a 36-inch Zagi airframe (tailless, elevons only configuration) is investigated and is the main focus of the report. Analytical methods, which include the use of the Advanced Aircraft Analysis software from DARCorp, were used to determine the stability and control derivatives, which were then validated through wind tunnel experiments. From the aerodynamic data, the linear, perturbed equations of motion from steady-state flight conditions may be cast in terms of these derivatives. Using these linear equations, transfer functions for the control and navigation systems were developed and feedback control laws based on Proportional, Integral, and Derivative (PID) control design were developed to control the aircraft. The PID gains may then be programmed into the autopilot software and uploaded to the microprocessor of the autopilot. The Pico-Pilot system was flight tested and shown to be successful in navigating a 12-inch MAV through a course defined by a number of waypoints with a high degree of accuracy, and in 20 mph winds. The system, though, showed problems with control authority in the roll and pitch motion of the aircraft: causing oscillations in these directions, but the aircraft maintained its heading while following the prescribed course. Flight tests were performed in remote control mode to evaluate handling, adjust trim, and test data logging for the Zagi with integrated MP2028(sup g). Ground testing was performed to test GPS acquisition, data logging, and control response in autonomous mode. Technical difficulties and integration limitations with the autopilot prevented fully autonomous flight from taking place, but the integration methodologies developed for this autopilot are, in general, applicable for unmanned air vehicles within the 36-inch size class or larger that use a PID control based autopilot.

Platanitis, George↗
DOE OSTI2025

Nuclear microreactor transient and load-following control with deep reinforcement learning

The economic feasibility of nuclear microreactors will depend on minimizing operating costs through advancements in autonomous control, especially when these microreactors are operating alongside other types of energy systems (e.g., renewable energy). This study explores the application of deep reinforcement learning (RL) for real-time drum control in microreactors, exploring performance in regard to load-following scenarios. By leveraging a point kinetics model with thermal and xenon feedback, we first establish a baseline using a single-output RL agent, then compare it against a traditional proportional–integral–derivative (PID) controller. This study demonstrates that RL controllers, including both single- and multi-agent RL (MARL) frameworks, can achieve similar or even superior load-following performance as traditional PID control across a range of load-following scenarios. In short transients, the RL agent was able to reduce the tracking error rate in comparison to PID by one half to one third. Over extended 300-minute load-following scenarios in which xenon feedback becomes a dominant factor, PID maintained better accuracy, but RL still remained within a 1% error margin despite being trained only on short-duration scenarios. This highlights RL’s strong ability to generalize and extrapolate to longer, more complex transients, affording substantial reductions in training costs and reduced overfitting. Furthermore, when control was extended to multiple drums, MARL enabled independent drum control as well as maintained reactor symmetry constraints without sacrificing performance---an objective that standard single-agent RL could not learn. We also found that, as increasing levels of Gaussian noise were added to the power measurements, the RL controllers were able to maintain lower error rates than PID, and to do so with at least 10% and upwards of 150% less control effort. These findings illustrate RL's potential for autonomous nuclear reactor control, laying the groundwork for future integration into high-fidelity simulations and experimental validation efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Application of step-response lambda tuning to proportional-integral controllers in water resource recovery facilities

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.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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 NTRS2008

Fault-Tolerant, Multiple-Zone Temperature Control

A computer program has been written as an essential part of an electronic temperature control system for a spaceborne instrument that contains several zones. The system was developed because the temperature and the rate of change of temperature in each zone are required to be maintained to within limits that amount to degrees of precision thought to be unattainable by use of simple bimetallic thermostats. The software collects temperature readings from six platinum resistance thermometers, calculates temperature errors from the readings, and implements a proportional + integral + derivative (PID) control algorithm that adjusts heater power levels. The software accepts, via a serial port, commands to change its operational parameters. The software attempts to detect and mitigate a host of potential faults. It is robust to many kinds of faults in that it can maintain PID control in the presence of those faults.

Granger, James↗
NASA NTRS2016

Closed Loop Control Compact Exercise Device for Use on MPCV

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. To combat spaceflight physiological deconditioning, astronauts will use resistive and aerobic exercise regimens for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the mass and volume available for an exercise device in the next generation of spacecraft is limited. Therefore, compact exercise device prototypes are being developed for human in the loop evaluations. The NASA Human Research Program (HRP) is managing Advanced Exercise Concepts (AEC) requirements development and candidate technology maturation for all exploration mission profiles from Multi-Purpose Crew Vehicle (MPCV) exploration missions (e.g., EM-2, up to 21 day) to Mars Transit (up to 1000 day) missions. Numerous technologies have been considered and evaluated against HRP-approved functional requirements and include flywheel, pneumatic and closed-loop microprocessor-controlled motor driven power plants. Motor driven technologies offer excellent torque density and load accuracy characteristics as well as the ability to create custom mechanical impedance (the dynamic relationship between force and velocity) and custom load versus position exercise algorithms. Further, closed-loop motor-driven technologies offer the ability to monitor exercise dose parameters and adapt to the needs of the crewmember for real time optimization of exercise prescriptions. A simple proportional-integral-derivative (PID) controller is demonstrated in a prototype motor driven exercise device with comparison to resistive static and dynamic load set points and aerobic work rate targets. The resistive load term in the algorithm includes a constant force component (Fcmg) as well as inertial component (Fima) and a discussion of system tuning is presented in terms of addressing key functional requirements and human interfaces. The device aerobic modality is modelled as a rowing exercise using ground data sets obtained from Concept 2 rowers as well as competitive rowing1. A discussion of software and electronic implementations are presented which demonstrate unique approaches to meeting the constrained mass, volume and power requirements of the MPCV. . In addition to utilizing traditional PID control, controllers utilizing state feedback with gains solved using a Linear Quadratic Regulator will be developed. Controllability and observability will be utilized to investigate the need for state measurement in the design. As the control system directly interacts with human test subjects, robust methods such as H-infinity are also being investigated.1. Kleshnev V. Biomechanics. In: Rowing, Handbook of Sports Medicine and Science. ed. by Secher N., Voliantis S. IOC Medical Commission, Blackwell Pub. pp. 22-34, 2007

microgravity↗
DOE OSTI2025

Reinforcement Learning Control for Buildings Co-Optimizing Energy, Comfort, and Indoor Air Quality: An Annual Assessment

Efficient control of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial for optimizing energy use and maintaining indoor comfort in buildings. Traditional control methods, such as PID control, cannot handle energy use trade-offs among multiple components in the building energy system at a supervisory level. Reinforcement learning (RL) presents a promising solution, offering adaptive and data-driven control strategies that optimize performance over time. However, RL also faces several challenges, including the conflicts encountered in co-optimizing energy savings, occupant comfort, and indoor air quality, and the requirement for extensive interactions with the environment in training. We proposed a flexible simulation platform that integrates a hybrid model for RL training and designed an RL agent to control the entire central HVAC system, focusing on co-optimizing energy consumption, thermal comfort, and indoor air quality ($\text{CO}_{2}$ and PM2.5 concentrations). Finally, we evaluated the RL agent's performance over an annual cycle. Our findings indicate that the RL agent can effectively manage the HVAC system with 14.7 % energy savings annually and balance multiple objectives, which demonstrates significant potential for improving HVAC system control and sustainability in buildings.

Guo, Fangzhou↗
NASA NTRS1991

Adaptive control of propellant slosh for a launch vehicle with multiple tanks

This paper discusses the use of an adaptive system to stabilize a multi-tank launch vehicle with sloshable fuel. The adaptive system utilizes a sensor to measure the fluid slosh angle, a recursive-least-squares estimator to estimate the natural frequency of the sloshing fuel, and a linear filter which stabilizes the unstable fuel slosh using the frequency estimate. Single-input and multiinput estimators were investigated. The time-varying complexity of the slosh control loop keeps the system persistently excited through flight, even though the attitude is controlled by a conventional PID controller. For the first portion of flight, the adaptive system maintains stability. A modification is proposed for latter portions of flight. The approach requires no tank baffles or partitions.

Saugen, John D.↗
DOE OSTI2023

Data-Driven Modeling of a High Capacity Cryogenic System for Control Optimization

The Cryogenic Moderator System (CMS) is responsible for maintaining a steady flow of cold neutrons for numerous physics experiments at the Spallation Neutron Source (SNS) in Oak Ridge National Laboratory (ORNL). Sudden losses in beam power, known as beam trips, cause a major disturbance to the CMS due to large step changes in cooling demands. Ongoing efforts on upgrading the neutron beam power from 1.4 to 2.0MW are expected to generate larger transients that can further strain the CMS subsystems if they are not properly controlled. To manage such disturbances, four flow valves and one electric heater are adjusted by five decentralized proportional-integral-derivative (PID) controllers. However, the original PID gains were calibrated empirically based only on tracking performance and not based on disturbance rejection. To address this issue without compromising current CMS operations, a control-oriented model was developed to recalibrate the PID controllers offline. The zero-dimensional (0-D) model was based on simple physics-based principles and data-driven system identification techniques. The CMS was broken into several subsystems for analysis, each of which corresponds to a parametric model tied to the thermodynamic states of the working fluid. The model parameters were identified using the nonlinear least squares method where the residuals were calculated from available sensor data. Simulation results show that the proposed model can capture the dynamics of the CMS at steady state and during beam trips.

Maldonado Puente, Bryan↗
NASA NTRS1990

A game theoretic controller for a linear time-invariant system with parameter uncertainty and its application to the Space Station

A game theoretic controller is developed for a linear time-invariant system with parameter uncertainties in system and input matrices. The input-output decomposition modeling for the plant uncertainty is adopted. The uncertain dynamic system is represented as an internal feedback loop in which the system is assumed forced by fictitious disturbance caused by the parameter uncertainty. By considering the input and the fictitious disturbance as two noncooperative players, a differential game problem is constructed. It is shown that the resulting time invariant controller stabilizes the uncertain system for a prescribed uncertainty bound. This game theoretic controller is applied to the momentum management and attitude control of the Space Station in the presence of uncertainties in the moments of inertia. Inclusion of the external disturbance torque to the design procedure results in a dynamical feedback controller which consists of conventional PID control and cyclic disturbance rejection filter. It is shown that the game theoretic design, comparing to the LQR design or pole placement design, improves the stability robustness with respect to inertia variations.

Rhee, Ihnseok↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
NASA NTRS1987

An adaptive control scheme for a flexible manipulator

The problem of controlling a single link flexible manipulator is considered. A self-tuning adaptive control scheme is proposed which consists of a least squares on-line parameter identification of an equivalent linear model followed by a tuning of the gains of a pole placement controller using the parameter estimates. Since the initial parameter values for this model are assumed unknown, the use of arbitrarily chosen initial parameter estimates in the adaptive controller would result in undesirable transient effects. Hence, the initial stage control is carried out with a PID controller. Once the identified parameters have converged, control is transferred to the adaptive controller. Naturally, the relevant issues in this scheme are tests for parameter convergence and minimization of overshoots during control switch-over. To demonstrate the effectiveness of the proposed scheme, simulation results are presented with an analytical nonlinear dynamic model of a single link flexible manipulator.

Yang, T. C.↗
NASA NTRSDate not supplied

Coding Structures for Seated Row Simulation of an Active Controlled Vibration Isolation and Stabilization System for Astronaut’s Exercise Platform

Simulation for seated aerobic row exercise was a continued task to assist NASA in analyzing a one-dimensional vibration isolation and stabilization system for astronaut’s exercise platform. Feedback delay and signal noise were added to the simulation model. Simulation runs for this study were conducted in two software simulation tools, Trick and MBDyn, software simulation environments developed at the NASA Johnson Space Center. The exciter force in the simulation was calculated from motion capture of an exerciser during a seated aerobic row exercise. The simulation runs include passive control, active control using a Proportional, Integral, Derivative (PID) controller, and active control using a Piecewise Linear Integral Derivative (PWLID) controller. Output parameters include displacements of the exercise platform, the exerciser, and the counterweight; transmitted force to the wall of spacecraft; and actuator force to the platform. The simulation results showed excellent force reduction in the active controlled system compared to the passive controlled system, which resulted in less force reduction.

Simulation↗
NASA NTRS2019

Testing of the Lunar Reconnaissance Orbiter Attitude Control System Re-Design Without a Gyro

The Lunar Reconnaissance Orbiter (LRO) was launched in 2009 and, with itsseven science instruments, has made numerous contributions to our understandingof the moon. LRO is in an elliptical, polar lunar orbit and nominally maintainsa nadir orientation. There are frequent slews off nadir to observe various sciencetargets. LRO attitude control system (ACS) has two star trackers and a gyro forattitude estimation in an extended Kalman filter (EKF) and four reaction wheelsused in a proportional-integral-derivative (PID) controller. LRO is equipped withthrusters for orbit adjustments and momentum management. In early 2018, thegyro was powered off following a fairly rapid decline in the laser intensity on theX axis. Without the gyro, the EKF has been disabled. Attitude is provided by asingle star tracker and a coarse rate estimate is computed by a back differencingof the star tracker quaternions. Slews have also been disabled. A new rate estimationapproach makes use of a complementary filter, combining the quaterniondifferentiated rates and the integrated PID limited control torque (with reactionwheel drag and feedforward torque removed). The filtered rate estimate replacesthe MIMU rate in the EKF, resulting in minimal flight software changes. The paperwill cover the preparation and testing of the new gyroless algorithm, both inground simulations and inflight.

Halverson, Julie↗
NASA NTRS1996

Nonlinear Multi-Window Controllers

In many control designs the error signal is split into parallel channels which are tailored to be significant over distinct frequency ranges and are then recombined. Often, at least one channel contains nonlinear elements, The most common example is a PID controller with an anti-windup nonlinearity in the I-channel. A more general example using higher-order compensators is presented, which is a thermal controller for a spacecraft-mounted telescope.

PID↗
NASA NTRS1990

Two Axis Pointing System (TAPS) attitude acquisition, determination, and control

The Two Axis Pointing System (TAPS) is a 2 axis gimbal system designed to provide fine pointing of Space Transportation System (STS) borne instruments. It features center-of-mass instrument mounting and will accommodate instruments of up to 1134 kg (2500 pounds) which fit within a 1.0 by 1.0 by 4.2 meter (40 by 40 by 166 inch) envelope. The TAPS system is controlled by a microcomputer based Control Electronics Assembly (CEA), a Power Distribution Unit (PDU), and a Servo Control Unit (SCU). A DRIRU-II inertial reference unit is used to provide incremental angles for attitude propagation. A Ball Brothers STRAP star tracker is used for attitude acquisition and update. The theory of the TAPS attitude determination and error computation for the Broad Band X-ray Telescope (BBXRT) are described. The attitude acquisition is based upon a 2 star geometric solution. The acquisition theory and quaternion algebra are presented. The attitude control combines classical position, integral and derivative (PID) control with techniques to compensate for coulomb friction (bias torque) and the cable harness crossing the gimbals (spring torque). Also presented is a technique for an adaptive bias torque compensation which adjusts to an ever changing frictional torque environment. The control stability margins are detailed, with the predicted pointing performance, based upon simulation studies. The TAPS user interface, which provides high level operations commands to facilitate science observations, is outlined.

Azzolini, John D.↗
NASA NTRS2001

Additive Runge-Kutta Schemes for Convection-Diffusion-Reaction Equations

Additive Runge-Kutta (ARK) methods are investigated for application to the spatially discretized one-dimensional convection-diffusion-reaction (CDR) equations. First, accuracy, stability, conservation, and dense output are considered for the general case when N different Runge-Kutta methods are grouped into a single composite method. Then, implicit-explicit, N = 2, additive Runge-Kutta ARK2 methods from third- to fifth-order are presented that allow for integration of stiff terms by an L-stable, stiffly-accurate explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method while the nonstiff terms are integrated with a traditional explicit Runge-Kutta method (ERK). Coupling error terms are of equal order to those of the elemental methods. Derived ARK2 methods have vanishing stability functions for very large values of the stiff scaled eigenvalue, z(exp [I]) goes to infinity, and retain high stability efficiency in the absence of stiffness, z(exp [I]) goes to zero. Extrapolation-type stage-value predictors are provided based on dense-output formulae. Optimized methods minimize both leading order ARK2 error terms and Butcher coefficient magnitudes as well as maximize conservation properties. Numerical tests of the new schemes on a CDR problem show negligible stiffness leakage and near classical order convergence rates. However, tests on three simple singular-perturbation problems reveal generally predictable order reduction. Error control is best managed with a PID-controller. While results for the fifth-order method are disappointing, both the new third- and fourth-order methods are at least as efficient as existing ARK2 methods while offering error control and stage-value predictors.

Kennedy, Christopher A.↗
NASA NTRS2002

Additive Runge-Kutta Schemes for Convection-Diffusion-Reaction Equations

Additive Runge-Kutta (ARK) methods are investigated for application to the spatially discretized one- dimensional convection-diffusion-reaction (CDR) equations. Accuracy, stability, conservation, and dense-output are first considered for the general case when N different Runge-Kutta methods are grouped into a single composite method. Then, implicit-explicit, (N = 2), additive Runge-Kutta (ARK(sub 2)) methods from third- to fifth-order are presented that allow for integration of stiff terms by an L-stable, stiffly-accurate explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method while the nonstiff terms are integrated with a traditional explicit Runge-Kutta method (ERK). Coupling error terms of the partitioned method are of equal order to those of the elemental methods. Derived ARK(sub 2) methods have vanishing stability functions for very large values of the stiff scaled eigenvalue, z['] yields -infinity, and retain high stability efficiency in the absence of stiffness, z['] yield 0. Extrapolation-type stage- value predictors are provided based on dense-output formulae. Optimized methods minimize both leading order ARK(sub 2) error terms and Butcher coefficient magnitudes as well as maximize conservation properties. Numerical tests of the new schemes on a CDR problem show negligible stiffness leakage and near classical order convergence rates. However, tests on three simple singular-perturbation problems reveal generally predictable order reduction. Error control is best managed with a PID-controller. While results for the fifth-order method are disappointing, both the new third- and fourth-order methods are at least as efficient as existing ARK(sub 2) methods.

Kennedy, Christopher A.↗