Modern control system theory and human control functions.
Modern optimal control theory relation to manual control systems emphasizing human element
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Modern optimal control theory relation to manual control systems emphasizing human element
Design concept for control system addresses how to prevent control inputs to plant from exceeding electrical limits imposed by mechanical limits of control actuators in plant, and prevent windup in integrators in control system. Concept consists of two parts. First, to rearrange terms of control equation to move integrators into output path of control system. Second, involves limiting inputs to integrators when one control input of plant reaches its limit. Concept applicable to control systems typical of aircraft autopilot systems.
Digital control systems for applications such as aircraft avionics and multibody systems must maintain adequate control integrity in adverse as well as nominal operating conditions. For example, control systems for advanced aircraft, and especially those with relaxed static stability, will be critical to flight and will, therefore, have very high reliability specifications which must be met regardless of operating conditions. In addition, multibody systems such as robotic manipulators performing critical functions must have control systems capable of robust performance in any operating environment in order to complete the assigned task reliably. Severe operating conditions for electronic control systems can result from electromagnetic disturbances caused by lightning, high energy radio frequency (HERF) transmitters, and nuclear electromagnetic pulses (NEMP). For this reason, techniques must be developed to evaluate the integrity of the control system in adverse operating environments. The most difficult and illusive perturbations to computer-based control systems that can be caused by an electromagnetic environment (EME) are functional error modes that involve no component damage. These error modes are collectively known as upset, can occur simultaneously in all of the channels of a redundant control system, and are software dependent. Upset studies performed to date have not addressed the assessment of fault tolerant systems and do not involve the evaluation of a control system operating in a closed-loop with the plant. A methodology for performing a real-time simulation of the closed-loop dynamics of a fault tolerant control system with a simulated plant operating in an electromagnetically harsh environment is presented. In particular, considerations for performing upset tests on the controller are discussed. Some of these considerations are the generation and coupling of analog signals representative of electromagnetic disturbances to a control system under test, analog data acquisition, and digital data acquisition from fault tolerant systems. In addition, a case study of an upset test methodology for a fault tolerant electromagnetic aircraft engine control system is presented.
A number of problems related to unmanned exploration of planets or other extraterrestrial bodies with Mars as a case in point were investigated. The design and evaluation of a prototype rover concept with emphasis on mobility, maneuverability, stability, control and propulsion is described along with the development of terrain sensor concepts and associated software for the autonomous control of any planetary rover. Results are applicable not only to the design of a mission rover but the vehicle is used as a test bed for the rigorous evaluation of alternative autonomous control systems.
The effects of winds, sideslip angle feedback, and the data reference (air or inertial) on the Reaction Control System (RCS) propellant requirements during entry were investigated. It was determined that in the presence of a 3 sigma crosswind an addition 188 pounds of RCS propellant was required for entry control which is within the present 200 pound allotment for winds. The absence of air data information does result in slightly higher RCS propellant demands.
Mission control center with network of ground stations to provide display, control and communication services
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NASA is developing the next generation launch vehicle that will take astronauts further into space than any previous manned vehicle. This project has many facets and one of them, the Spaceport Command and Control System (SCCS), was the primary focus of my work during this internship. A vital ability of SCCS is the communication from the firing rooms to the ground support equipment for the vehicle on the launch pad. During this internship, I was part of the Computer Systems Hardware Team, a group of engineers who handle the computer and networking aspects of the SCCS project. My job was to construct, handle, and test computer and network machines, configurations and cables.
From the control point of view, spacecraft are classified into two main groups: those for which the spacecraft is fully defined before the control system is designed; and those for which the control system must be specified before certain interchangeable parts of a multi-purpose spacecraft are selected for future missions. Consideration is given to both classes of problems.
HARPS is a telerobot control system that can perform some simple but useful tasks. This capability is demonstrated by performing the ORU exchange demonstration. HARPS is based on NASREM (NASA Standard Reference Model). All software is developed in Ada, and the project incorporates a number of different CASE (computer-aided software engineering) tools. NASREM was found to be a valid and useful model for building a telerobot control system. Its hierarchical and distributed structure creates a natural and logical flow for implementing large complex robust control systems. The ability of Ada to create and enforce abstraction enhanced the implementation of such control systems.
Nose-mounted control-system jets in roll-control positions effect on aerodynamics of space vehicle
A controller for a series hybrid capillary pumped loop (CPL) system that requires no moving parts does not resrict fluid flow has been tested and has demonstrated improved performance characteristics over a plain CPL system and simple hybrid CPL systems. These include heat load sharing, phase separation, self-regulated flow control and distribution, all independent of most system pressure drop. In addition, the controlled system demonstrated a greater heat transport capability than the simple CPL system but without the large fluid inventory requirement of the hybrid systems. A description of the testing is presented along with data that show the advantages of the system.
A vehicle includes a chassis, a modular component, and a central operating system. The modular component is supported by the chassis. The central operating system includes a component control system, a primary master controller, and a secondary master controller. The component control system is configured for controlling the modular component. The primary and secondary master controllers are in operative communication with the component control system. The primary and secondary master controllers are configured to simultaneously transmit commands to the component control system. The component control system is configured to accept commands from the secondary master controller only when a fault occurs in the primary master controller.
A backup flight control system for controlling the flightpath of a multi-engine airplane using the main drive engines is introduced. The backup flight control system comprises an input device for generating a control command indicative of a desired flightpath, a feedback sensor for generating a feedback signal indicative of at least one of pitch rate, pitch attitude, roll rate and roll attitude, and a control device for changing the output power of at least one of the main drive engines on each side of the airplane in response to the control command and the feedback signal.
Flight control system design factors involved for pilot workload relief are identified. Major contributors to pilot workload include configuration management and control and aircraft stability and response qualities. A digital fly by wire stability augmentation, configuration management, and configuration control system is suggested for reduction of pilot workload during takeoff, hovering, and approach.
The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.
An aircraft control system is described which is particularly suited to rotary wing aircraft. Longitudinal acceleration and course rate commands are derived from a manual control stick to control translational velocity of the aircraft along a flight path. In the collective channel the manual controls provide vertical velocity commands. In the yaw channel the manual controls provide sideslip or heading rate commands at high or low airspeeds, respectively. The control system permits pilots to fly along prescribed flight paths in a precise manner with relatively low work load.
A thermal control system was incorporated into the Lunar Roving Vehicle (LRV) to maintain temperature sensitive components within appropriate temperature limits during the translunar transportation phase, lunar surface operation, and quiescent periods between lunar traverses. This paper describes the thermal control system and discusses its thermal characteristics during all phases of operation. The basic concept is a passive system which stores internally generated energy during operation with subsequent radiation to space. The external environments are regulated by selected radiative surface finishes. Multi-layer insulation blankets, space radiators, flexible thermal straps, and fusible mass heat sinks were designed to control the temperatures of the electronic components.