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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Class 2 design update for the family of commuter airplanes

This is the final report of seven on the design of a family of commuter airplanes. This design effort was performed in fulfillment of NASA/USRA grant NGT-8001. Its contents are as follows: (1) the class 1 baseline designs for the commuter airplane family; (2) a study of takeoff weight penalties imposed on the commuter family due to implementing commonality objectives; (3) component structural designs common to the commuter family; (4) details of the acquisition and operating economics of the commuter family, i.e., savings due to production commonality and handling qualities commonality are determined; (5) discussion of the selection of an advanced turboprop propulsion system for the family of commuter airplanes, and (6) a proposed design for an SSSA controller design to achieve similar handling for all airplanes. Final class 2 commuter airplane designs are also presented.

Creighton, Thomas R.↗
NASA NTRS1989

A NASTRAN/TREETOPS solution to a flexible, multi-body dynamics and controls problem on a UNIX workstation

Demands for nonlinear time history simulations of large, flexible multibody dynamic systems has created a need for efficient interfaces between finite-element modeling programs and time-history simulations. One such interface, TREEFLX, an interface between NASTRAN and TREETOPS, a nonlinear dynamics and controls time history simulation for multibody structures, is presented and demonstrated via example using the proposed Space Station Mobile Remote Manipulator System (MRMS). The ability to run all three programs (NASTRAN, TREEFLX and TREETOPS), in addition to other programs used for controller design and model reduction (such as DMATLAB and TREESEL, both described), under a UNIX Workstation environment demonstrates the flexibility engineers now have in designing, developing and testing control systems for dynamically complex systems.

Benavente, Javier E.↗
NASA NTRS1991

A two-time-scale autopilot for high-performance aircraft

A two-time-scale autopilot is proposed for the Aircraft Controls Design Challenge problem. This control law uses a nonlinear aircraft model constructed from the given vehicle simulation. The vehicle model is partitioned into slow translational dynamics and fast rotational dynamics. Feedback linearization is then employed to synthesize control laws for these two-time scales. Due to the nature of the synthesis, the control law is suitable for automatic trajectory following, and also for pilot control.

Menon, P. K. A.↗
NASA NTRS1990

Flight control system design factors for applying automated testing techniques

The principal design features and operational experiences of the X-29 forward-swept-wing aircraft and F-18 high alpha research vehicle (HARV) automated test systems are discussed. It is noted that operational experiences in developing and using these automated testing techniques have highlighted the need for incorporating target system features to improve testability. Improved target system testability can be accomplished with the addition of nonreal-time and real-time features. Online access to target system implementation details, unobtrusive real-time access to internal user-selectable variables, and proper software instrumentation are all desirable features of the target system. Also, test system and target system design issues must be addressed during the early stages of the target system development. Processing speeds of up to 20 million instructions/s and the development of high-bandwidth reflective memory systems have improved the ability to integrate the target system and test system for the application of automated testing techniques. It is concluded that new methods of designing testability into the target systems are required.

Sitz, Joel R.↗
NASA NTRS1991

Integrated adaptive filtering and design for control experiments of flexible structures

A novel method is presented of identifying a state space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relations between the state space model and the finite difference model for linear stochastic systems derived through projection filters. It is proven that least squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model. In estimating the corresponding state estimator gain, a z-domain method is used. First the deterministic component of the output is subtracted out, and then the state estimator gain is obtained by whitening the remaining signal. Experimental example is used to illustrate the feasibility of the method.

Huang, Jen-Kuang↗
NASA NTRS1993

A Darwinian approach to control-structure design

Genetic algorithms (GA's), as introduced by Holland (1975), are one form of directed random search. The form of direction is based on Darwin's 'survival of the fittest' theories. GA's are radically different from the more traditional design optimization techniques. GA's work with a coding of the design variables, as opposed to working with the design variables directly. The search is conducted from a population of designs (i.e., from a large number of points in the design space), unlike the traditional algorithms which search from a single design point. The GA requires only objective function information, as opposed to gradient or other auxiliary information. Finally, the GA is based on probabilistic transition rules, as opposed to deterministic rules. These features allow the GA to attack problems with local-global minima, discontinuous design spaces and mixed variable problems, all in a single, consistent framework.

Zimmerman, David C.↗
NASA NTRS2002

On-Line Computation of a Local Attainable Moment Set for Reusable Launch Vehicles

Traditional attitude control design of reusable launch vehicles involves independent design of autopilot and control allocation modules [SBB99], [SK97], [SHJ00], [PS00], [Hod00]. Unfortunately, this results in the potential for overly aggressive commands in the autopilot resulting in a loss of performance due to actuator saturation, particularly if the autopilot may suffer from integrator wind-up [HH01].

Hodel, A. S.↗
NASA NTRS2001

Design and Control of Large Collections of Learning Agents

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

Agogino, Adrian↗
NASA NTRS2005

Integration of an Autopilot for a Micro Air Vehicle

Two autopilots providing autonomous flight capabilities are presented herein. The first is the Pico-Pilot, demonstrated for the 12-inch size class of micro air vehicles. The second is the MicroPilot MP2028(sup g), where its integration into a 36-inch Zagi airframe (tailless, elevons only configuration) is investigated and is the main focus of the report. Analytical methods, which include the use of the Advanced Aircraft Analysis software from DARCorp, were used to determine the stability and control derivatives, which were then validated through wind tunnel experiments. From the aerodynamic data, the linear, perturbed equations of motion from steady-state flight conditions may be cast in terms of these derivatives. Using these linear equations, transfer functions for the control and navigation systems were developed and feedback control laws based on Proportional, Integral, and Derivative (PID) control design were developed to control the aircraft. The PID gains may then be programmed into the autopilot software and uploaded to the microprocessor of the autopilot. The Pico-Pilot system was flight tested and shown to be successful in navigating a 12-inch MAV through a course defined by a number of waypoints with a high degree of accuracy, and in 20 mph winds. The system, though, showed problems with control authority in the roll and pitch motion of the aircraft: causing oscillations in these directions, but the aircraft maintained its heading while following the prescribed course. Flight tests were performed in remote control mode to evaluate handling, adjust trim, and test data logging for the Zagi with integrated MP2028(sup g). Ground testing was performed to test GPS acquisition, data logging, and control response in autonomous mode. Technical difficulties and integration limitations with the autopilot prevented fully autonomous flight from taking place, but the integration methodologies developed for this autopilot are, in general, applicable for unmanned air vehicles within the 36-inch size class or larger that use a PID control based autopilot.

Platanitis, George↗
NASA NTRS1993

Design and Control of the MESUR/Pathfinder Microrover

The use of unmanned robotic vehicles to assist in the exploration of Mars and other planets has been of interest to the National Aeronautics and Space Administration (NASA) for several decades and has been the focus of an ongoing research program at the Jet Propulsion Laboratory (JPL) for a similar period of time.

MESUR/Pathfinder↗