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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Feedback Linearized Aircraft Control Using Dynamic Cell Structure

A Dynamic Cell Structure (DCS ) Neural Network was developed which learns a topology representing network (TRN) of F-15 aircraft aerodynamic stability and control derivatives. The network is combined with a feedback linearized tracking controller to produce a robust control architecture capable of handling multiple accident and off-nominal flight scenarios. This paper describes network and its performance for accident scenarios including differential stabilator lock, soft sensor failure, control, stability derivative variation, and turbulence.

Jorgensen, C. C.↗
NASA NTRS2007

Robust Fuzzy Controllers Using FPGAs

Electro-mechanical device controllers typically come in one of three forms, proportional (P), Proportional Derivative (PD), and Proportional Integral Derivative (PID). Two methods of control are discussed in this paper; they are (1) the classical technique that requires an in-depth mathematical use of poles and zeros, and (2) the fuzzy logic (FL) technique that is similar to the way humans think and make decisions. FL controllers are used in multiple industries; examples include control engineering, computer vision, pattern recognition, statistics, and data analysis. Presented is a study on the development of a PD motor controller written in very high speed hardware description language (VHDL), and implemented in FL. Four distinct abstractions compose the FL controller, they are the fuzzifier, the rule-base, the fuzzy inference system (FIS), and the defuzzifier. FL is similar to, but different from, Boolean logic; where the output value may be equal to 0 or 1, but it could also be equal to any decimal value between them. This controller is unique because of its VHDL implementation, which uses integer mathematics. To compensate for VHDL's inability to synthesis floating point numbers, a scale factor equal to 10(sup (N/4) is utilized; where N is equal to data word size. The scaling factor shifts the decimal digits to the left of the decimal point for increased precision. PD controllers are ideal for use with servo motors, where position control is effective. This paper discusses control methods for motion-base platforms where a constant velocity equivalent to a spectral resolution of 0.25 cm(exp -1) is required; however, the control capability of this controller extends to various other platforms.

Monroe, Author Gene S., Jr.↗
NASA NTRS2005

Robust Load-Sharing Control of Spacecraft Formations

This paper focuses on the design of autonomous and collaborative control strategies to govern the relative distances among multiple spacecraft in formation with no ground intervention. A coordinate load-sharing control structure for formation flying and a methodology to control their dynamic models with slow time-varying and uncertain parameters are the main objectives of this work. The method is applied to a deep space formation example, where the uncertainty in spacecraft fuel masses is also considered.

multi spacecraft↗
NASA NTRS2003

Stochastic Control Synthesis of Systems with Structured Uncertainty

This paper presents a study on the design of robust controllers by using random variables to model structured uncertainty for both SISO and MIMO feedback systems. Once the parameter uncertainty is prescribed with probability density functions, its effects are propagated through the analysis leading to stochastic metrics for the system's output. Control designs that aim for satisfactory performances while guaranteeing robust closed loop stability are attained by solving constrained non-linear optimization problems in the frequency domain. This approach permits not only to quantify the probability of having unstable and unfavorable responses for a particular control design but also to search for controls while favoring the values of the parameters with higher chance of occurrence. In this manner, robust optimality is achieved while the characteristic conservatism of conventional robust control methods is eliminated. Examples that admit closed form expressions for the probabilistic metrics of the output are used to elucidate the nature of the problem at hand and validate the proposed formulations.

Padula, Sharon L.↗
NASA NTRS1989

Holographic signal processing for control of a flexible beam

A robust control system is presented for damping vibrations in a cantilevered beam. The distributed deflections of the beam are sensed using real-time holography. A hybrid processor which uses optical and digital processors is proposed to implement a distributed control algorithm. The controller is designed using the linear-quadratic-Gaussian method to add damping to a finite number of vibrational modes.

Barsky, Michael F.↗
NASA NTRS2005

A First and Second Order Moment Approach to Probabilistic Control Synthesis

This paper presents a robust control design methodology based on the estimation of the first two order moments of the random variables and processes that describe the controlled response. Synthesis is performed by solving an multi-objective optimization problem where stability and performance requirements in time- and frequency domains are integrated. The use of the first two order moments allows for the efficient estimation of the cost function thus for a faster synthesis algorithm. While reliability requirements are taken into account by using bounds to failure probabilities, requirements related to undesirable variability are implemented by quantifying the concentration of the random outcome about a deterministic target. The Hammersley Sequence Sampling and the First- and Second-Moment- Second-Order approximations are used to estimate the moments, whose accuracy and associated computational complexity are compared numerically. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Crespo, Luis G.↗
NASA NTRS1990

Robust H(infinity) control design for the Space Station with structured parameter uncertainty

A robust H(infinity) control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multiparameter variations in the state-space formulation of H(infinity) control theory. An application of this robust control synthesis technique tothe Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this new robust H(infinity) controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.

Byun, Kuk-Whan↗
NASA NTRS1991

Intelligent failure-tolerant control

An overview of failure-tolerant control is presented, beginning with robust control, progressing through parallel and analytical redundancy, and ending with rule-based systems and artificial neural networks. By design or implementation, failure-tolerant control systems are 'intelligent' systems. All failure-tolerant systems require some degrees of robustness to protect against catastrophic failure; failure tolerance often can be improved by adaptivity in decision-making and control, as well as by redundancy in measurement and actuation. Reliability, maintainability, and survivability can be enhanced by failure tolerance, although each objective poses different goals for control system design. Artificial intelligence concepts are helpful for integrating and codifying failure-tolerant control systems, not as alternatives but as adjuncts to conventional design methods.

Stengel, Robert F.↗
NASA NTRS1992

Robust dynamic inversion control laws for aircraft control

Dynamic inversion is a technique for control law design in which feedback is used to simultaneously cancel system dynamics and achieve desired dynamic response characteristics. However, dynamic inversion control laws lack robustness to modeling errors if improperly designed. This paper examines a simple linear example, control of roll rate about the body axis of high performance aircraft, to illustrate some robustness problems which may occur with a simple dynamic inversion control law. The paper demonstrates how structured singular value synthesis techniques can be used to enhance the robustness properties of the dynamic inversion controller.

Balas, Gary J.↗
NASA NTRS1993

Robust algebraic image enhancement for intelligent control systems

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

Lerner, Bao-Ting↗
NASA NTRS2000

Sliding Mode Control of the X-33 with an Engine Failure

Ascent flight control of the X-3 is performed using two XRS-2200 linear aerospike engines. in addition to aerosurfaces. The baseline control algorithms are PID with gain scheduling. Flight control using an innovative method. Sliding Mode Control. is presented for nominal and engine failed modes of flight. An easy to implement, robust controller. requiring no reconfiguration or gain scheduling is demonstrated through high fidelity flight simulations. The proposed sliding mode controller utilizes a two-loop structure and provides robust. de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of engine failure, bounded external disturbances (wind gusts) and uncertain matrix of inertia. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues. Conditions that restrict engine failures to robustness domain of the sliding mode controller are derived. Overall stability of a two-loop flight control system is assessed. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in the presence of external disturbances and vehicle inertia uncertainties, as well as the single engine failed case. The designed robust controller will significantly reduce the time and cost associated with flying new trajectory profiles or orbits, with new payloads, and with modified vehicles

Shtessel, Yuri B.↗
NASA NTRS1986

Control design for robust stability in linear regulators: Application to aerospace flight control

Time domain stability robustness analysis and design for linear multivariable uncertain systems with bounded uncertainties is the central theme of the research. After reviewing the recently developed upper bounds on the linear elemental (structured), time varying perturbation of an asymptotically stable linear time invariant regulator, it is shown that it is possible to further improve these bounds by employing state transformations. Then introducing a quantitative measure called the stability robustness index, a state feedback conrol design algorithm is presented for a general linear regulator problem and then specialized to the case of modal systems as well as matched systems. The extension of the algorithm to stochastic systems with Kalman filter as the state estimator is presented. Finally an algorithm for robust dynamic compensator design is presented using Parameter Optimization (PO) procedure. Applications in a aircraft control and flexible structure control are presented along with a comparison with other existing methods.

Yedavalli, R. K.↗
NASA NTRS1991

Frequency domain identification for robust large space structure control design

A methodology is demonstrated for frequency domain identification of large space structures which systematically transforms experimental raw data into a form required for synthesizing H(infinity) controllers using modern robust control design software (e.g., Matlab Toolboxes). A unique feature of this approach is that the additive uncertainty is characterized to a specified statistic confidence rather than with hard bounds. In this study, the difference in robust performance is minimal between the two levels of confidence. In general cases, the present methodology provides a tool for performance/confidence level tradeoff studies. For simplicity, the additive uncertainty on a frequency grid is considered and the interpolation error in between grid points is neglected.

Yam, Y.↗