A study of adaptive multimode systems Final technical report, Mar. 1967 - Apr. 1968
Laboratory model of experiment for demonstrating applicability of adaptive multimode systems concept to scientific spacecraft instrumentation
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Laboratory model of experiment for demonstrating applicability of adaptive multimode systems concept to scientific spacecraft instrumentation
Park adaptive control system design extended to multivariable systems
This paper presents the development and analysis of a wavefront control strategy for a dense adaptive optics system with segmented primary mirror.
An adaptive observer for multivariable systems of order n having p output measurements is developed. The adaptive observer allows both the generation of the state of the system and - at least - the partial identification of the unknown parameters of the system. The order of this adaptive observer is n - p plus 1. The adaptive algorithm, based upon Liapunov synthesis, may be implemented in real time without the use of derivative operators. Eigenvalues of the observer may be arbitrarily or almost arbitrarily located. With some mild restriction upon the structure of the multivariable system, and upon the command system input, both generation of state and identification of parameters is guaranteed globally.
Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.
In recent flight tests of F-15 Intelligent Flight Control System (IFCS), software simulated aircraft control surface failures were inserted to evaluate the IFCS adaptive systems. The failure commanded the left stabilator to a fixed position. The adaptive system uses a neural network that is designed to change control law gains, in the event of damage (real or simulated), that allows the aircraft to fly as it had before the damage. The performance of the adaptive system was assessed in terms of its ability to re-establish good onboard model tracking and its ability to decouple roll and pitch response.
Error correcting codes and data compression techniques for PCM adaptive telemetry systems - abstracts
Based on a recent model of evolving viruses competing with an adapting immune system, we study the conditions under which a viral quasispecies can maximize its growth rate.
In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. We have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. We develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, our algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures.
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.
We present the design and performance of a Concurrent Artificially-intelligent Spectrometry and Adaptive Lidar System (CASALS) for 3D imaging from Space. With a single fast wavelength tuning laser, CASALS accomplishes a 1,200 resolvable spots swath mapping by grating dispersion wavelength steering. Any subset of these 1,200 spots can be selected by wavelength switching. The validation operating principle was accomplished and reported in IGASS-2022. With configurable base design, we report the designs and progress of the CASALS airplane campaign with 256 contiguous ground spots. It is accomplished with a single fast tuning lase at 1040-nm, 1.152MHz tuning rate, and pulse modulated 2-ns on each wavelength. Return pulses are mapped to an eight-pixel detector array with single-photon sensitivity. The lidar returns are time-multiplexed to two outputs that are digitized with two 1-GSPS-digitizer. A grating spectrometer rejects solar background noise spatially and spectrally. We are developing a 1040-nm CASALS intended for multiple LEO orbit missions: Earth Venture Mission on ESPA Grande, STV Mission on ESPA Grande SmallSat, STV Mission on spacecraft equivalent to ICESat power (SWaP,) and splitting the laser beam requires higher laser pulse energy.
The objective of this joint activity between Kennedy Space Center (KSC) and Glenn Research Center (GRC) is to develop and evaluate the applicability of 2-way SMAs in proof-of-concept, low-temperature adaptive autonomous systems. As part of this low technology readiness (TRL) activity, we will develop and train low-temperature novel, 2-way shape memory alloys (SMAs) with actuation temperatures ranging from 0 C to 150 C. These experimental alloys will also be preliminary tested to evaluate their performance parameters and transformation (actuation) temperatures in low- temperature or cryogenic adaptive proof-of-concept systems. The challenge will be in the development, design, and training of the alloys for 2-way actuation at those temperatures.
It is shown that persistent excitation (PE) conditions are overly stringent for ensuring exponential convergence of the tracking error in overparametrized adaptive feedforward systems.
In the Shuttle era, it should be possible to develop adaptive remote sensor systems serving more directly specific researcher and user needs and at the same time alleviating the data management problem via intelligent sensor capabilities. The present paper provides a summary of such an approach, wherein specific capabilities have been developed for future global monitoring applications. A detailed description of FILE-I (Feature Identification and Location Experiment) is included along with a summary of future experiments currently under development.
We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.
Adaptation of Titan II liquid propellant rocket engine for Gemini program
In order to execute the Vision for Space Exploration, we must find ways to reduce cost, system complexity, design, build, and test times, and at the same time increase flexibility to satisfy multiple functions. Modular, Adaptive, Reconfigurable System (MARS) technologies promise to set the stage for the delivery of system elements that form the building blocks of increasingly ambitious missions involving humans and robots. Today, space systems are largely specialized and built on a case-by-case basis. The notion of modularity however, is nothing new to NASA. The 1970's saw the development of the Multi-Mission Modular spacecraft (MMS). From 1980 to 1992 at least six satellites were built under this paradigm, and included such Goddard Space Flight Center missions as SSM, EUVE, UARS, and Landsat 4 and 5. Earlier versions consisted of standard subsystem "module" or "box" components that could be replaced within a structure based on predefined form factors. Although the primary motivation for MMS was faster/cheaper integration and test, standardization of interfaces, and ease of incorporating new subsystem technology, it lacked the technology maturity and programmatic "upgrade infrastructure" needed to satisfy varied mission requirements, and ultimately it lacked user buy-in. Consequently, it never evolved and was phased out. Such concepts as the Rapid Spacecraft Development Office (RSDO) with its regularly updated catalogue of prequalified busses became the preferred method for acquiring satellites. Notwithstanding, over the past 30 years since MMS inception, technology has advanced considerably and now modularity can be extended beyond the traditional MMS module or box to cover levels of integration, from the chip, card, box, subsystem, to the space system and to the system-of-systems. This paper will present the MARS architecture, cast within the historical context of MMS. Its application will be highlighted by comparing a state-of-the-art point design vs. a MARS-enabled lunar mission, as a representative robotic case design.
The dynamic properties and the mathematical model for the adaptive control of the robotic system presently under investigation at Robotic Application and Development Laboratory at Kennedy Space Center are discussed. NASA is currently investigating the use of robotic manipulators for mating and demating of fuel lines to the Space Shuttle Vehicle prior to launch. The Robotic system used as a testbed for this purpose is an ASEA IRB-90 industrial robot with adaptive control capabilities. The system was tested and it's performance with respect to stability was improved by using an analogue force controller. The objective of this research project is to determine the mathematical model of the system operating under force feedback control with varying dynamic internal perturbation in order to provide continuous stable operation under variable load conditions. A series of lumped parameter models are developed. The models include some effects of robot structural dynamics, sensor compliance, and workpiece dynamics.