SEARCH · Search NASA
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.
A flight control system design is presented, that can be implemented by analog hardware, to be used to control an aircraft with uncertain parameters. The design is based upon the use of modern control theory. The ideas are illustrated by considering control of STOL longitudinal dynamics.
The Vehicle Control Systems Team at Marshall Space Flight Center, Systems Dynamics Laboratory, Guidance and Control Systems Division is designing under a cooperative agreement with Lockheed Martin Skunkworks, the Ascent, Transition, and Entry flight attitude control system for the X-33 experimental vehicle. Ascent flight control begins at liftoff and ends at linear aerospike main engine cutoff (NECO) while Transition and Entry flight control begins at MECO and concludes at the terminal area energy management (TAEM) interface. TAEM occurs at approximately Mach 3.0. This task includes not only the design of the vehicle attitude control systems but also the development of requirements for attitude control system components and subsystems. The X-33 attitude control system design is challenged by a short design cycle, the design environment (Mach 0 to about Mach 15), and the X-33 incremental test philosophy. The X-33 design-to-launch cycle of less than 3 years requires a concurrent design approach while the test philosophy requires design adaptation to vehicle variations that are a function of Mach number and mission profile. The flight attitude control system must deal with the mixing of aerosurfaces, reaction control thrusters, and linear aerospike engine control effectors and handle parasitic effects such as vehicle flexibility and propellant sloshing from the uniquely shaped propellant tanks. The attitude control system design is, as usual, closely linked to many other subsystems and must deal with constraints and requirements from these subsystems.
Adaptive flight control systems hold tremendous promise for maintaining the safety of a damaged aircraft and its passengers. However, most currently proposed adaptive control methodologies rely on online learning neural networks (OLNNs), which necessarily have the property that the controller is changing during the flight. These changes tend to be highly nonlinear, and difficult or impossible to analyze using standard techniques. In this paper, we approach the problem with a variant of compositional verification. The overall system is broken into components. Undesirable behavior is fed backwards through the system. Components which can be solved using formal methods techniques explicitly for the ranges of safe and unsafe input bounds are treated as white box components. The remaining black box components are analyzed with heuristic techniques that try to predict a range of component inputs that may lead to unsafe behavior. The composition of these component inputs throughout the system leads to overall system test vectors that may elucidate the undesirable behavior
Controls systems are an increasingly important component of turbine-engine system technology. However, as engines become more capable, the control system itself becomes ever more constrained by the inherent environmental conditions of the engine; a relationship forced by the continued reliance on commercial electronics technology. A revolutionary change in the architecture of turbine-engine control systems will change this paradigm and result in fully distributed engine control systems. Initially, the revolution will begin with the physical decoupling of the control law processor from the hostile engine environment using a digital communications network and engine-mounted high temperature electronics requiring little or no thermal control. The vision for the evolution of distributed control capability from this initial implementation to fully distributed and embedded control is described in a roadmap and implementation plan. The development of this plan is the result of discussions with government and industry stakeholders
A monitoring system and methods are provided for a distributed and recoverable digital control system. The monitoring system generally comprises two independent monitoring planes within the control system. The first monitoring plane is internal to the computing units in the control system, and the second monitoring plane is external to the computing units. The internal first monitoring plane includes two in-line monitors. The first internal monitor is a self-checking, lock-step-processing monitor with integrated rapid recovery capability. The second internal monitor includes one or more reasonableness monitors, which compare actual effector position with commanded effector position. The external second monitor plane includes two monitors. The first external monitor includes a pre-recovery computing monitor, and the second external monitor includes a post recovery computing monitor. Various methods for implementing the monitoring functions are also disclosed.
Description of an automatic control system for high-intensity acoustic tests in reverberation chambers. Working in 14 one-third-octave bands from 50 to 1000 Hz, the desired sound pressure levels are set into the memory in the control system before the test. The control system then increases the sound pressure level in the reverberation chamber gradually in each of the one-third-octave bands until the level set in the memory is reached. This level is then maintained for the duration of the test. Additional features of the system are overtest protection, the capability of 'holding' the spectrum at any time, and the presence of a total test timer.
An improved methodology for designing feedback control systems has been developed based on systematically shaping the loop gain of the system to meet performance requirements such as stability margins, disturbance attenuation, and transient response, while taking into account the actuation system limitations such as actuation rates and range. Loop-shaping for controls design is not new, but past techniques do not directly address how to systematically design the controller to maximize its performance. As a result, classical feedback control systems are designed predominantly using ad hoc control design approaches such as proportional integral derivative (PID), normally satisfied when a workable solution is achieved, without a good understanding of how to maximize the effectiveness of the control design in terms of competing performance requirements, in relation to the limitations of the plant design. The conception of this improved methodology was motivated by challenges in designing control systems of the types needed for supersonic propulsion. But the methodology is generally applicable to any classical control-system design where the transfer function of the plant is known or can be evaluated. In the case of a supersonic aerospace vehicle, a major challenge is to design the system to attenuate anticipated external and internal disturbances, using such actuators as fuel injectors and valves, bypass doors, and ramps, all of which are subject to limitations in actuator response, rates, and ranges. Also, for supersonic vehicles, with long slim type of structures, coupling between the engine and the structural dynamics can produce undesirable effects that could adversely affect vehicle stability and ride quality. In order to design distributed controls that can suppress these potential adverse effects, within the full capabilities of the actuation system, it is important to employ a systematic control design methodology such as this that can maximize the effectiveness of the control design in a methodical and quantifiable way. The emphasis is in generating simple but rather powerful design techniques that will allow even designers with a layman s knowledge in controls to develop effective feedback control designs. Unlike conventional ad hoc methodologies of feedback control design, in this approach actuator rates are incorporated into the design right from the start: The relation between actuator speeds and the desired control bandwidth of the system is established explicitly. The technique developed is demonstrated via design examples in a step-by-step tutorial way. Given the actuation system rates and range limits together with design specifications in terms of stability margins, disturbance rejection, and transient response, the procedure involves designing the feedback loop gain to meet the requirements and maximizing the control system effectiveness, without exceeding the actuation system limits and saturating the controller. Then knowing the plant transfer function, the procedure involves designing the controller so that the controller transfer function together with the plant transfer function equate to the designed loop gain. The technique also shows what the limitations of the controller design are and how to trade competing design requirements such as stability margins and disturbance rejection. Finally, the technique is contrasted against other more familiar control design techniques, like PID control, to show its advantages.
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.
The application of system identification methods to high-bandwidth rotorcraft flight control system design is examined. Flight test and modeling requirements are illustrated using flight test data from a BO-105 hingeless rotor helicopter. The proposed approach involves the identification of nonparametric frequency-response models followed by parametric (transfer funtion and state space) model identification. Results for the BO-105 show the need for including coupled body/rotor flapping and lead-lag dynamics in the identification model structure to allow the accurate prediction of control system bandwidth limitations. Lower-order models are useful for estimating nominal control system performance only when the flight data used for the identification are band-limited to be consistent with the frequency range of applicability of the model. The flight test results presented in this paper are consistent with theoretical studies by previous researchers.
Flight control system of Saturn V launch vehicle, discussing attitude/attitude-rate scheme, gain required and stability achieved
A frequency control system makes an initial correction of the frequency of its own timing circuit after comparison against a frequency of known accuracy and then sequentially checks and corrects the frequencies of several voltage controlled local oscillator circuits. The timing circuit initiates the machine cycles of a central processing unit which applies a frequency index to an input register in a modulo-sum frequency divider stage and enables a multiplexer to clock an accumulator register in the divider stage with a cyclical signal derived from the oscillator circuit being checked. Upon expiration of the interval, the processing unit compares the remainder held as the contents of the accumulator against a stored zero error constant and applies an appropriate correction word to a correction stage to shift the frequency of the oscillator being checked. A signal from the accumulator register may be used to drive a phase plane ROM and, with periodic shifts in the applied frequency index, to provide frequency shift keying of the resultant output signal. Interposition of a phase adder between the accumulator register and phase plane ROM permits phase shift keying of the output signal by periodic variation in the value of a phase index applied to one input of the phase adder.
The INteractive Controls Analysis (INCA) program was developed at the Goddard Space Flight Center to provide a user friendly efficient environment for the design and analysis of linear control systems. Since its inception, INCA has found extensive use in the design, development, and analysis of control systems for spacecraft, instruments, robotics, and pointing systems. Moreover, the results of the analytic tools imbedded in INCA have been flight proven with at least three currently orbiting spacecraft. This paper describes the INCA program and illustrates, using a flight proven example, how the package can perform complex design analyses with relative ease.
Flight control system of Saturn V launch vehicle, discussing attitude/attitude rate scheme, gain required and stability achieved
The Spartan attitude control system (ACS) control electronics assembly cold plate has a standard connector interface to the rest of the Spartan payload and ground equipment. The connectors carry gyro signals, optical sensor signals, the experiment interface, the gas command decoder interface, and a pneumatics interface. Different flights can employ different optical sensor complements; the ACS engineer must accordingly connect the sensor error signals to the proper pins and connectors on the ACS electronics.
Insensitive flight control system design criteria was defined in terms of maximizing performance (handling qualities, RMS gust response, transient response, stability margins) over a defined parameter range. Wing load alleviation for the C-5A was chosen as a design problem. The C-5A model was a 79-state, two-control structure with uncertainties assumed to exist in dynamic pressure, structural damping and frequency, and the stability derivative, M sub w. Five new techniques (mismatch estimation, uncertainty weighting, finite dimensional inverse, maximum difficulty, dual Lyapunov) were developed. Six existing techniques (additive noise, minimax, multiplant, sensitivity vector augmentation, state dependent noise, residualization) and the mismatch estimation and uncertainty weighting techniques were synthesized and evaluated on the design example. Evaluation and comparison of these six techniques indicated that the minimax and the uncertainty weighting techniques were superior to the other six, and of these two, uncertainty weighting has lower computational requirements. Techniques based on the three remaining new concepts appear promising and are recommended for further research.
I helped the Launch Control System (LCS) hardware team sustain the network design of the Spaceport Command and Control System. I wrote the procedure that will be used to satisfy an official hardware test for the hardware carrying data from the Launch Vehicle. I installed hardware and updated design documents in support of the ongoing development of the Spaceport Command and Control System and applied firewall experience I gained during my spring 2017 semester to inspect and create firewall security policies as requested. Finally, I completed several online courses concerning networking fundamentals and Unix operating systems.
Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment.