Pneumatic logic rocket engine sequence control.
Fluidic breadboard version of rocket engine sequence control, describing pneumatic logic package and general limitations
FLUIDICS↗
SEARCH · Search NASA
Results for “control sequences”
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.
Pneumatic logic rocket engine sequence control.
Fluidic breadboard version of rocket engine sequence control, describing pneumatic logic package and general limitations
Milleman, S. E.↗
A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system
There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.
Hein, C.↗
Digital Sequence Controller
Length and timing of pulse sequences user controlled. Digital circuit generates several pulse streams to control loads that must be synchronized allowing duration and phasing of each stream to be varied independently. Application of circuit to control pump for biomedical applications.
Lonborg, J. O.↗
Fast Control Sequencer
Unit faster than conventional circuits and contains fewer integrated circuits. Fast logic controller accommodates three delays before second half cycle of clock signal strobes status latch: Outputs of pipeline register must settle; selected input status line signal must propagate through status multiplexer and arrive at status latch; and it takes 3 nanoseconds for status latch set up before strobed. During second half cycle, output-enable line produces next instruction and applies it to pipeline register.
Lahmeyer, C. R.↗
Serial data correlator/code translator
A system for analyzing asynchronous signals containing bits of information for ensuring the validity of said signals, by sampling each bit of information a plurality of times, and feeding the sampled pieces of bits of information into a sequence controlled is described. The sequence controller has a plurality of maps or programs through which the sampled pieces of bits are stepped so as to identify the particular bit of information and determine the validity and phase of the bit. The step in which the sequence controller is clocked is controlled by a storage register. A data decoder decodes the information fed out of the storage register and feeds such information to shift registers for storage.
Morgan, L. E.↗
Programmable controller system for wind tunnel diversion vanes
A programmable controller (PC) system automatic sequence control, which acts as a supervisory controller for the servos, selects the proper drives, and automatically sequences the vanes, was developed for use in a subsonic wind tunnel. Tunnel modifications include a new second test section (80 ft x 100 ft with a maximum air speed capability of 110 knots) and an increase in maximum velocity flow from 200 knots to 300 knots. A completely automatic sequence control is necessary in order to allow intricate motion of the 14 triangularly arranged vanes which can be as large as 70 ft high x 35 ft wide and which require precise acceleration and deceleration control. Rate servos on each drive aid in this control, and servo cost was minimized by using four silicon controlled rectifier controllers to control the 20 dc drives. The PC has a programming capacity which facilitated the implementation of extensive logic design. A series of diagrams sequencing the vanes and a block diagram of the system are included.
King, R. F.↗
Viking adaptive mission sequence and control operations
Viking mission operations were required to provide an adaptive sequencing capability in which future observations could be influenced by the latest information about Mars as it was obtained and analyzed. The mission operations strategy that was developed met this requirement and provided the capability to respond smoothly and efficiently to spacecraft subsystem anomalies with minimum impact on the science data gathering process. A description of the major elements of this adaptive man-in-the-loop control system is provided. Specific cases showing how it was utilized to enhance scientific return and to respond to spacecraft anomalies are also provided.
Larman, B. T.↗
Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Feature Map
A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a Self Organizing Feature Map (SOFM). Local linear modeling of nonlinear autonomous systems with the SOFM is extended to a control framework where the modeled system is nonautonomous, driven by an exogenous input. This extension to a control framework is based on the consideration of a finite number of subregions in the control space. Multiple self organizing feature maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experimental knowledge gained from decades of operation. Each SOFM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOFM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal. Each SOFM provides a codebook representation of the tunnel dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the minimization of a similarity metric which is the essence of the self organizing feature of the map. Thus, the SOFM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme than selects the best available model for the applied control. Experimental results of controlling the wind tunnel, with the proposed method, during operational runs where strict research requirements on the control of the Mach number were met, are presented. Comparison to similar runs under the same conditions with the tunnel controlled by either the existing controller or an expert operator indicate the superiority of the method.
Motter, Mark A.↗
Control of the NASA Langley 16-Foot Transonic Tunnel with the Self-Organizing Map
A predictive, multiple model control strategy is developed based on an ensemble of local linear models of the nonlinear system dynamics for a transonic wind tunnel. The local linear models are estimated directly from the weights of a self-organizing map (SOM). Multiple self-organizing maps collectively model the global response of the wind tunnel to a finite set of representative prototype controls. These prototype controls partition the control space and incorporate experiential knowledge gained from decades of operation. Each SOM models the combination of the tunnel with one of the representative controls, over the entire range of operation. The SOM based linear models are used to predict the tunnel response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
Mark A. Motter↗
Predictive Multiple Model Switching Control with the Self-Organizing Map
A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.
Motter, Mark A.↗
An analytic study of near terminal area optimal sequencing and flow control techniques
Optimal flow control and sequencing of air traffic operations in the near terminal area are discussed. The near terminal area model is based on the assumptions that the aircraft enter the terminal area along precisely controlled approach paths and that the aircraft are segregated according to their near terminal area performance. Mathematical models are developed to support the optimal path generation, sequencing, and conflict resolution problems.
Park, S. K.↗
A parallel row-based algorithm with error control for standard-cell replacement on a hypercube multiprocessor
A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.
Sargent, Jeff Scott↗
Computational alternatives to obtain time optimal jet engine control
Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.
Basso, R. J.↗
Method of damping nutation motion with minimum spin axis attitude disturbance
In a method of and apparatus for damping nutation of a spinning spacecraft, spin axis attitude disturbances are substantially reduced by controlling at least one nutation damping gas thruster to fire with nonuniform gas pulses. During the beginning of a nutation control sequence, the duration of successive gas pulses is gradually increased (up pulsed) from zero to a predetermined maximum duration. The duration of successive pulses is then maintained constant for a time period. Finally, at the end of the nutation control sequence, the duration of successive gas pulses is gradually reduced to zero (down pulsed). Up pulsing of the gas thruster is initiated in response to a predetermined maximum nutation angle measured by an accelerometer. Down pulsing of the thruster is initiated in response to a predetermined minimum nutation angle.
Hoffman, H. C.↗
Automatic sequencing and control of Space Station airlock operations
Procedures that have been developed as part of the NASA JSC-sponsored pre-prototype Checkout, Servicing and Maintenance (COSM) program for pre- and post-EVA airlock operations are described. This paper addresses the accompanying pressure changes in the airlock and in the Advanced Extravehicular Mobility Unit (EMU). Additionally, the paper focuses on the components that are checked out, and includes the step-by-step sequences to be followed by the crew, the required screen displays and prompts that accompany each step, and a description of the automated processes that occur.
Himel, Victor↗
Proof of quasi-adaptivity for the m-measurement feedback class of stochastic control policies
Bounds on expected performance are established which show that the m-measurement feedback (mM) policy for nonlinear stochastic control performs as well or better than the open-loop optimal control policy, and thus is quasi-adaptive in the sense of Witenhausen (1966). The chain of performance inequalities indicate a tendency for the mM policy performance to improve with increasing m. It is suggested that the present analytical method, based on the construction of artificial control sequences denoted as utility controls, can be used to establish performance bounds on other well-known policies, avoiding the extensive Monte Carlo simulations necessary in comparing stochastic control policies.
Bayard, David S.↗
Using Mach threads to control DSN operational sequences
The Link Monitor and Control Operator Assistant prototype (LMCOA) is a state-of-the-art, semiautomated monitor and control system based on an object-oriented design. The purpose of the LMCOA prototyping effort is to both investigate new technology (such as artificial intelligence) to support automation and to evaluate advances in information systems toward developing systems that take advantage of the technology. The emergence of object-oriented design methodology has enabled a major change in how software is designed and developed. This paper describes how the object-oriented approach was used to design and implement the LMCOA and the results of operational testing. The LMCOA is implemented on a NeXT workstation using the Mach operating system and the Objective-C programming language.
Urista, Juan↗