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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A control scheme for trajectory tracking of robot manipulators

The authors put forward a simple scheme for multivariable control of robot manipulators. The scheme is composed of an inner-loop stabilizing controller and an outerloop tracking controller. The inner loop utilizes a multivariable PD (proportional differential) controller to stabilize the robot by placing the poles at some desired locations. The outer loop uses a multivariable PID (proportional integral differential) controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated online to cope with variations in the robot model for gross motion and payload change. Alternatively, the use of high-gain controllers for gross motion and payload change are discussed.

Tarokh, M.↗
NASA NTRS1989

On the populating mechanisms of the autoionising states of Al III ions produced in a Penning ionisation discharge

Spectra emitted by Al II and Al III in the 100-1900-A range from a Penning ionization discharge (PID) have been analyzed in order to study the populating mechanisms of the autoionizing levels of the Al III ion. Electron temperature and density estimates and Al III line intensities obtained using a collisional-radiative model are found to differ from those obtained experimentally, implying that the autoionizing levels of the Na I-like ion may be populated, in the PID plasma, by the inner-shell ionization of excited Mg I-like ions. It is suggested that such autoionizing lines could be used to search for populations inversions in the soft X-ray domain.

Finkenthal, M.↗
NASA NTRS1990

An expert system to perform on-line controller tuning

An expert system which tunes a Proportional-Integral-Derivative (PID) controller on-line for a single-input-single-output multiple-lag process with dead time is described. The expert system examines features of the previous transient responses and their corresponding sets of controller parameters. It determines a new set of controller gains to obtain a more desirable time response. This technique can be used to determine and implement a different set of PID gains for each operating regime and, once in steady state, the system can be used to find optimal parameters for load disturbance rejection. The expert system can be applied to any system of the specified form (aerospace, industrial, etc.) and can be expanded to include additional process models.

Litt, Jonathan S.↗
NASA NTRS1991

A multivariable control scheme for robot manipulators

The article puts forward a simple scheme for multivariable control of robot manipulators to achieve trajectory tracking. The scheme is composed of an inner loop stabilizing controller and an outer loop tracking controller. The inner loop utilizes a multivariable PD controller to stabilize the robot by placing the poles of the linearized robot model at some desired locations. The outer loop employs a multivariable PID controller to achieve input-output decoupling and trajectory tracking. The gains of the PD and PID controllers are related directly to the linearized robot model by simple closed-form expressions. The controller gains are updated on-line to cope with variations in the robot model during gross motion and for payload change. Alternatively, the use of high gain controllers for gross motion and payload change is discussed. Computer simulation results are given for illustration.

Tarokh, M.↗
NASA NTRS1990

An expert system to perform on-line controller tuning

An expert system which tunes a proportional-integral-derivative (PID) controller online for a single-input-single-output multiple-lag process with dead time is described. The expert system examines features of the previous transient responses and their corresponding sets of controller parameters. It determines a new set of controller gains to obtain a more desirable time response. This technique can be used to determine and implement a different set of PID gains for each operating regime and, once in steady state, the system can be used to find optimal parameters for load disturbance rejection. The expert system can be applied to any system of the specified form (aerospace, industrial, etc.) and can be expanded to include additional process models.

Litt, Jonathan↗
NASA NTRS1992

Determination of the stability and control derivatives of the F/A-18 HARV from flight data using the maximum likelihood method

The research being conducted pertains to the determination of the stability and control derivatives of the F/A-18 High Alpha Research Vehicle (HARV) from flight data using the Maximum Likelihood Method. The document outlines the approach used in the parameter estimation (PID) process and briefly describes the mathematical modeling of the F/A-18 HARV and the maneuvers designed to generate a sufficient data base for the PID research.

Napolitano, Marcello R.↗
NASA NTRS1993

Design issues for a reinforcement-based self-learning fuzzy controller

Fuzzy logic controllers have some often cited advantages over conventional techniques such as PID control: easy implementation, its accommodation to natural language, the ability to cover wider range of operating conditions and others. One major obstacle that hinders its broader application is the lack of a systematic way to develop and modify its rules and as result the creation and modification of fuzzy rules often depends on try-error or pure experimentation. One of the proposed approaches to address this issue is self-learning fuzzy logic controllers (SFLC) that use reinforcement learning techniques to learn the desirability of states and to adjust the consequent part of fuzzy control rules accordingly. Due to the different dynamics of the controlled processes, the performance of self-learning fuzzy controller is highly contingent on the design. The design issue has not received sufficient attention. The issues related to the design of a SFLC for the application to chemical process are discussed and its performance is compared with that of PID and self-tuning fuzzy logic controller.

Yen, John↗
NASA NTRS1992

Design issues of a reinforcement-based self-learning fuzzy controller for petrochemical process control

Fuzzy logic controllers have some often-cited advantages over conventional techniques such as PID control, including easier implementation, accommodation to natural language, and the ability to cover a wider range of operating conditions. One major obstacle that hinders the broader application of fuzzy logic controllers is the lack of a systematic way to develop and modify their rules; as a result the creation and modification of fuzzy rules often depends on trial and error or pure experimentation. One of the proposed approaches to address this issue is a self-learning fuzzy logic controller (SFLC) that uses reinforcement learning techniques to learn the desirability of states and to adjust the consequent part of its fuzzy control rules accordingly. Due to the different dynamics of the controlled processes, the performance of a self-learning fuzzy controller is highly contingent on its design. The design issue has not received sufficient attention. The issues related to the design of a SFLC for application to a petrochemical process are discussed, and its performance is compared with that of a PID and a self-tuning fuzzy logic controller.

Yen, John↗
NASA NTRS1992

Control-structure interaction

The feasibility of using conventional proportional-integral-derivative (PID) control and an alternative optimal control to perform the pointing and tracking functions of the Space Station solar dynamic power module is investigated. A very large state model of 6 rigid body modes and 272 flexible modes is used in conjunction with classical linear-quadratic-Gaussian (LQG) optimal control to produce a full-order controller that satisfies the requirements. The results are compared with a classically designed PID controller that was implemented for a much smaller (6 rigid body, 40 flexible modes) model. The conventional control design approach is shown to be very much influenced by the order reduction of the plant model, i.e., the number of retained elastic modes from the full-order model, suggesting that for a complex, large space structure, such as the Space Station Freedom solar dynamic module, application of conventional control system design methods may not be adequate. The use of LQG control is recommended, and method for solving the large matrix. Riccati equation that arises from the optimal formulation is provided.

Cheng, Joseph K.↗
NASA NTRS1994

Three-parameter tunable Tilt-Integral-Derivative (TID) controller

A feedback control system compensator of the PID type is provided, wherein the proportional component of the compensator is replaced with a tilted component having a transfer function s to the power of -1/n. The resulting transfer function of the entire compensator more closely approximates an optimal transfer function, thereby achieving improved feedback controller. Further, as compared to conventional PID compensators, the TID compensator allows for simpler tuning, better disturbance rejection ratio, and smaller effects of plant parameter variations on closed loop response.

Lurie, Boris J.↗
NASA NTRS1994

Neural net controller for inlet pressure control of rocket engine testing

Many dynamic systems operate in select operating regions, each exhibiting characteristic modes of behavior. It is traditional to employ standard adjustable gain proportional-integral-derivative (PID) loops in such systems where no apriori model information is available. However, for controlling inlet pressure for rocket engine testing, problems in fine tuning, disturbance accommodation, and control gains for new profile operating regions (for research and development) are typically encountered. Because of the capability of capturing I/O peculiarities, using NETS, a back propagation trained neural network is specified. For select operating regions, the neural network controller is simulated to be as robust as the PID controller. For a comparative analysis, the higher order moment neural array (HOMNA) method is used to specify a second neural controller by extracting critical exemplars from the I/O data set. Furthermore, using the critical exemplars from the HOMNA method, a third neural controller is developed using NETS back propagation algorithm. All controllers are benchmarked against each other.

Trevino, Luis C.↗
NASA NTRS1995

Expendable launch vehicle studies

Analytical support studies of expendable launch vehicles concentrate on the stability of the dynamics during launch especially during or near the region of maximum dynamic pressure. The in-plane dynamic equations of a generic launch vehicle with multiple flexible bending and fuel sloshing modes are developed and linearized. The information from LeRC about the grids, masses, and modes is incorporated into the model. The eigenvalues of the plant are analyzed for several modeling factors: utilizing diagonal mass matrix, uniform beam assumption, inclusion of aerodynamics, and the interaction between the aerodynamics and the flexible bending motion. Preliminary PID, LQR, and LQG control designs with sensor and actuator dynamics for this system and simulations are also conducted. The initial analysis for comparison of PD (proportional-derivative) and full state feedback LQR Linear quadratic regulator) shows that the split weighted LQR controller has better performance than that of the PD. In order to meet both the performance and robustness requirements, the H(sub infinity) robust controller for the expendable launch vehicle is developed. The simulation indicates that both the performance and robustness of the H(sub infinity) controller are better than that for the PID and LQG controllers. The modelling and analysis support studies team has continued development of methodology, using eigensensitivity analysis, to solve three classes of discrete eigenvalue equations. In the first class, the matrix elements are non-linear functions of the eigenvector. All non-linear periodic motion can be cast in this form. Here the eigenvector is comprised of the coefficients of complete basis functions spanning the response space and the eigenvalue is the frequency. The second class of eigenvalue problems studied is the quadratic eigenvalue problem. Solutions for linear viscously damped structures or viscoelastic structures can be reduced to this form. Particular attention is paid to Maxwell and Kelvin models. The third class of problems consists of linear eigenvalue problems in which the elements of the mass and stiffness matrices are stochastic. dynamic structural response for which the parameters are given by probabilistic distribution functions, rather than deterministic values, can be cast in this form. Solutions for several problems in each class will be presented.

Bainum, Peter M.↗
NASA NTRS1997

Construction and Modeling of a Controls Testbed

This paper describes the construction and modeling of a control system testbed to be used for the comparison of various control methodologies. We specifically wish to test fuzzy logic control and compare performance of various fuzzy controllers, including Hybrid Fuzzy-PID (HFPID) and Hierarchical Hybrid Fuzzy-PID (HHFPID) to other controllers including localized rate feedback, LQR/LTR, and H2/H(sub infinity). The control problem is that of vibration suppression in a thin plate with inputs coming from accelerometers and outputs going to piezoelectric actuators or 'patches'. A model based on experimental modal analysis of the plate is conducted and compared with an analytical model. The analytical model uses a boundary condition which is a mix of clamped and simply supported.

Nagle, James C.↗
NASA NTRS1982

Handling Qualities Specifications for U.S. Military Helicopters

Inadequacies in the military specification for helicopter handling qualities, MIL-H-8501A, have long been recognized, and the latest procurements by the U.S. Army used special Prime Item Development Specifications (PIDS). This paper assesses the efficacy of these PIDS and suggests that changes should be made. In particular, the structure developed in MIL-F-8785B (ASG) (the specification for flying qualities of piloted airplanes) should be incorporated. Improved requirements must be based on a systematic data base and concentrated on topics most important in preliminary design: static and dynamic stability, control power and sensitivity, and interaction with controllers and displays. Emphasis should be on current military helicopter missions and helicopter idiosyncrasies such as cross-coupling, nonlinearities, and higher-order dynamics.

Key, David L.↗
NASA NTRS1995

Genetic Adaptive Control for PZT Actuators

A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.

Kim, Jeongwook↗
NASA NTRS2003

GPS Auto-Navigation Design for Unmanned Air Vehicles

A GPS auto-navigation system is designed for Unmanned Air Vehicles. The objective is to enable the air vehicle to be used as a test-bed for novel flow control concepts. The navigation system uses pre-programmed GPS waypoints. The actual GPS position, heading, and velocity are collected by the flight computer, a PC104 system running in Real-Time Linux, and compared with the desired waypoint. The navigator then determines the necessity of a heading correction and outputs the correction in the form of a commanded bank angle, for a level coordinated turn, to the controller system. This controller system consists of 5 controller! (pitch rate PID, yaw damper, bank angle PID, velocity hold, and altitude hold) designed for a closed loop non-linear aircraft model with linear aerodynamic coefficients. The ability and accuracy of using GPS data, is validated by a GPS flight. The autopilots are also validated in flight. The autopilot unit flight validations show that the designed autopilots function as designed. The aircraft model, generated on Matlab SIMULINK is also enhanced by the flight data to accurately represent the actual aircraft.

Nilsson, Caroline C. A.↗
NASA NTRS2000

Postural control model interpretation of stabilogram diffusion analysis

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS2005

Simulation Analysis of Computer-Controlled pressurization for Mixture Ratio Control

A procedural code (C++) simulation was developed to investigate potentials for mixture ratio control of pressure-fed spacecraft rocket propulsion systems by measuring propellant flows, tank liquid quantities, or both, and using feedback from these measurements to adjust propellant tank pressures to set the correct operating mixture ratio for minimum propellant residuals. The pressurization system eliminated mechanical regulators in favor of a computer-controlled, servo- driven throttling valve. We found that a quasi-steady state simulation (pressure and flow transients in the pressurization systems resulting from changes in flow control valve position are ignored) is adequate for this purpose. Monte-Carlo methods are used to obtain simulated statistics on propellant depletion. Mixture ratio control algorithms based on proportional-integral-differential (PID) controller methods were developed. These algorithms actually set target tank pressures; the tank pressures are controlled by another PID controller. Simulation indicates this approach can provide reductions in residual propellants.

Alexander, Leslie A.↗