On synthesis of sampled-data control systems
Synthesis method of sampled data control systems on basis of frequency pattern
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Synthesis method of sampled data control systems on basis of frequency pattern
Saturn launch vehicle flight control system model based on rigid-body control law
A regenerable CO2 and humidity control system is presently being developed for potential use on shuttle as an alternative to the baseline lithium hydroxide system. The system utilizes a sorbent material (designated HS-C) to adsorb CO2 and the latent heat load from the cabin atmosphere and desorb the CO2 and water vapor overboard when exposed to a space vacuum, thus reducing the overall vehicle heat rejection load. Continuous operation is achieved by utilizing two beds which are alternatively cycled between adsorption and desorption. The HS-C material process was verified. Design concepts for the auxiliary components for the HS-C prototype system were generated. Performance testing verified system effectiveness in controlling CO2 partial pressure and humidity.
The characteristics of a digital-analog hybrid system composed of a DJS-8 digital computer and a HMJ-200 analog computer are described as well as its applications to simulation research for an automatic flight control system. A hybrid computational example is included to illustrate the application.
A spacecraft attitude and/or velocity control system includes a controller which responds to at least attitude errors to produce command signals representing a force vector F and a torque vector T, each having three orthogonal components, which represent the forces and torques which are to be generated by the thrusters. The thrusters may include magnetic torquer or reaction wheels. Six difference equations are generated, three having the form ##EQU1## where a.sub.j is the maximum torque which the j.sup.th thruster can produce, b.sub.j is the maximum force which the j.sup.th thruster can produce, and .alpha..sub.j is a variable representing the throttling factor of the j.sup.th thruster, which may range from zero to unity. The six equations are summed to produce a single scalar equation relating variables .alpha..sub.j to a performance index Z: ##EQU2## Those values of .alpha. which maximize the value of Z are determined by a method for solving linear equations, such as a linear programming method. The Simplex method may be used. The values of .alpha..sub.j are applied to control the corresponding thrusters.
The design of a propulsion and steering control system for the Rensselaer Polytechnic Institute prototype autonomous Mars roving vehicle is presented. The vehicle is propelled and steered by four independent electric motors. The control system must regulate the speeds of the motors so they work in unison during turns and on irregular terrain. An analysis of the motor coordination problem on irregular terrain, where each motor must supply a different torque at a different speed is presented. A procedure was developed to match the output of each motor to the varying load. A design for the control system is given. The controller uses a microprocessor which interprets speed and steering commands from an off-board computer, and produces the appropriate drive voltages for the motors.
Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.
As aircraft designs trend toward further applications of control-configured vehicle concepts, aircraft control systems increasingly rely on stability augmentation to obtain normal flying qualities and reasonable structural margins. Although the control system designer would choose to have a perfect dynamic description of the vehicle, he knows that a level of uncertainty of plant dynamics will exist. This paper gives typical values of plant uncertainties for some recent aircraft design and development programs. Histories of pertinent aerodynamic, inertial, and structural parameters from program initiation to aircraft certification are given. These data can be used as typical of future vehicles so that control system design concepts can be evaluated with due consideration to their sensitivity to uncertainties in plant dynamics.
Comparisons are presented analytically predicted and experimental turbulence responses of a wind tunnel model of a DC-10 derivative wing equipped with an active control system. The active control system was designed for the purpose of flutter suppression, but it had additional benefit of alleviating gust loads (wing bending moment) by about 25%. Comparisions of various wing responses are presented for variations in active control system parameters and tunnel speed. The analytical turbulence responses were obtained using DYLOFLEX, a computer program for dynamic loads analyses of flexible airplanes with active controls. In general, the analytical predictions agreed reasonably well with the experimental data.
A control system for an electromagnetic rotary drive for bearingless motor-generators comprises a winding configuration comprising a plurality of individual pole pairs through which phase current flows, each phase current producing both a lateral force and a torque. A motor-generator comprises a stator, a rotor supported for movement relative to the stator, and a control system. The motor-generator comprises a winding configuration supported by the stator. The winding configuration comprises at least three pole pairs through which phase current flows resulting in three three-phase systems. Each phase system has a first rotor reference frame axis current that produces a levitating force with no average torque and a second rotor reference frame axis current that produces torque.
A control system for an electromagnetic rotary drive for bearingless motor-generators comprises a winding configuration comprising a plurality of individual pole pairs through which phase current flows, each phase current producing both a lateral force and a torque. A motor-generator comprises a stator, a rotor supported for movement relative to the stator, and a control system. The motor-generator comprises a winding configuration supported by the stator. The winding configuration comprises at least three pole pairs through which phase current flows resulting in three three-phase systems. Each phase system has a first rotor reference frame axis current that produces a levitating force with no average torque and a second rotor reference frame axis current that produces torque.
A triplex digital flight control system was installed in a NASA F-8C airplane to provide fail operate, full authority control. The triplex digital computers and interface circuitry process the pilot commands and aircraft motion feedback parameters according to the selected control laws, and they output the surface commands as an analog signal to the servoelectronics for position control of the aircraft's power actuators. The system and theory of operation of the computer by pass and servoelectronics are described and an automated ground test for each axis is included.
Failure analysis methods for aircraft automatic flight control systems
The design of a reaction control system (RCS) for the Large Space Telescope is discussed. The primary requirement for the RCS is to serve as an emergency backup control system to the primary attitude control system. A regulated gaseous nitrogen RCS was selected. The operation of the system and its individual components is described. The principal design goals of the RCS were to minimize contamination effects, make use of existing components, and modularize the system to provide ease in manned orbital maintenance.
A conceptual design of the control system for Payload Pointing Systems (PPS) is developed using classic Proportional-Integral-Derivatives (PID) techniques. The major source of system pointing error is due to the disturbance-rich environment of the space station in the form of gimbal baseplate motions. These baseplate vibrations are characterized using Fast Fourier Transform (FFT) techniques. Both time domain and frequency domain dynamic models are developed to assess control system performance. Three basic methods exist for the improvement of PPS pointing performance: increase control system bandwidth, add Image Motion Compensation, and/or reduce (or change) the baseplate disturbance environment.
Text on stability of control system as developed from direct method of Liapunov, noting V. M. Popov contribution
The project titled “Developing an Energy-Conscious Traffic Signal Control System for Optimized Fuel Consumption in Connected Vehicle Environments” addresses energy-related challenges associated with adaptive traffic control systems by integrating connected vehicles (CV) and connected infrastructure (CI). The system developed in this project, a CV-based adaptive traffic control system, aims to improve fuel consumption in mixed traffic environments by capitalizing on emerging CV and CI communication technologies, as well as leveraging recent advances in Artificial Intelligence (AI), optimization, and edge computing. The system was tested at the MLK Smart Corridor, an urban testbed managed by the University of Tennessee at Chattanooga (UTC) and the City of Chattanooga. The system was validated through extensive simulations, both Software-in-the-Loop (SILS) and Hardware-in-the-Loop (HILS), and was further implemented and tested in real-world conditions at several intersections along the corridor. The Fuel Consumption Performance Index (FC-PI) and the Ecological Performance Index (Eco-PI) were developed as the key components for evaluating the system’s impact on fuel consumption and emissions. These metrics provided a comprehensive means of understanding the impact of traffic signal control optimization in mixed traffic environments. The report presents an in-depth analysis of the Eco-PI, FC-PI, adaptive traffic control system integration, and the testing and field implementation of the system. The results demonstrate significant reductions in fuel consumption and emissions, showcasing the system’s capability to contribute to more sustainable urban traffic management. The report also documents the challenges encountered and recommendations for scaling and further improving the system.
Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.