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155 records · Page 9

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NASA NTRS2012

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Nguyen, Nhan T.↗

NASA NTRS1993

Determination of the mass properties of a manipulator

Space applications for telerobotics requires a manipulator that is robust to the large payload variations that occur in a zero-g environment. One approach to provide the required performance for this large payload variation is to provide inertial decoupling to the controller. The equations to generate the required joint torques can be obtained in several manners but the independent parameters required to perform the calculations are difficult to obtain. This presentation consists of an overview of the inertial decoupling control system and discusses how to reduce the inertial parameter set to a minimum and obtain the required parameter set to a minimum and obtain the required parameter vector using sensed joint positions and torques. In addition, as telerobotic technology becomes more prevalent in the space environments the ability to emulate the effect of zero-g in a one-g environment is critical in learning how to perform tasks in space. To emulate the zero-g environment it is necessary to remove the effect of gravity on the manipulator by determining the feedforward joint torques. A subset of the algorithm developed to obtain the decoupling parameters is used to obtain the gravity offload parameters. These parameters are used to eliminate the effect of gravity. The algorithm is validated on Martin Marietta/NASA Langley's, 7 Degrees-Of-Freedom (DOF) Flight Telerobotic Servicer Hydraulic Manipulator Test Bed. A video portraying actual results of the algorithm is provided.

Goldenberg, Stewart↗

NASA NTRS1991

Neural network application to aircraft control system design

The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design.

Troudet, Terry↗

NASA NTRS1991

Neural network application to aircraft control system design

The feasibility of using artificial neural network as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research identified to enhance the practical applicability of neural networks to flight control design.

Troudet, Terry↗

NASA NTRS2007

Entry Attitude Controller for the Mars Science Laboratory

This paper describes the preliminary concept for the RCS 3-axis attitude controller for the exo-atmospheric and guided entry phases of the Mars Science Laboratory Entry, Descend and Landing. The entry controller is formulated as three independent channels in the control frame, which is nominally aligned with the stability frame. Each channel has a feedfoward and a feedback. The feedforward path enables fast response to large bank commands. The feedback path stabilizes the vehicle angle of attack and sideslip around its trim position, and tracks bank commands. The feedback path has a PD/D structure with deadbands that minimizes fuel usage. The performance of this design is demonstrated via simulation.

Mars↗

NASA NTRS2009

Hybrid NN/SVM Computational System for Optimizing Designs

A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily oversimplified to fit the scope of this article, an SVM can be characterized as an algorithm that (1) effects a nonlinear mapping of input vectors into a higher-dimensional feature space and (2) involves a dual formulation of governing equations and constraints. One advantageous feature of the SVM approach is that an objective function (which one seeks to minimize to obtain coefficients that define an SVM mathematical model) is convex, so that unlike in the cases of many NN models, any local minimum of an SVM model is also a global minimum.

Rai, Man Mohan↗

NASA NTRS2019

Testing of the Lunar Reconnaissance Orbiter Attitude Control System Re-Design Without a Gyro

The Lunar Reconnaissance Orbiter (LRO) was launched in 2009 and, with itsseven science instruments, has made numerous contributions to our understandingof the moon. LRO is in an elliptical, polar lunar orbit and nominally maintainsa nadir orientation. There are frequent slews off nadir to observe various sciencetargets. LRO attitude control system (ACS) has two star trackers and a gyro forattitude estimation in an extended Kalman filter (EKF) and four reaction wheelsused in a proportional-integral-derivative (PID) controller. LRO is equipped withthrusters for orbit adjustments and momentum management. In early 2018, thegyro was powered off following a fairly rapid decline in the laser intensity on theX axis. Without the gyro, the EKF has been disabled. Attitude is provided by asingle star tracker and a coarse rate estimate is computed by a back differencingof the star tracker quaternions. Slews have also been disabled. A new rate estimationapproach makes use of a complementary filter, combining the quaterniondifferentiated rates and the integrated PID limited control torque (with reactionwheel drag and feedforward torque removed). The filtered rate estimate replacesthe MIMU rate in the EKF, resulting in minimal flight software changes. The paperwill cover the preparation and testing of the new gyroless algorithm, both inground simulations and inflight.

Halverson, Julie↗

NASA NTRS1989

Stability analysis of multiple-robot control systems

In a space telerobotic service scenario, cooperative motion and force control of multiple robot arms are of fundamental importance. Three paradigms to study this problem are proposed. They are distinguished by the set of variables used for control design. They are joint torques, arm tip force vectors, and an accelerated generalized coordinate set. Control issues related to each case are discussed. The latter two choices require complete model information, which presents practical modeling, computational, and robustness problems. Therefore, focus is on the joint torque control case to develop relatively model independent motion and internal force control laws. The rigid body assumption allows the motion and force control problems to be independently addressed. By using an energy motivated Lyapunov function, a simple proportional derivative plus gravity compensation type of motion control law is always shown to be stabilizing. The asymptotic convergence of the tracing error to zero requires the use of a generalized coordinate with the contact constraints taken into account. If a non-generalized coordinate is used, only convergence to a steady state manifold can be concluded. For the force control, both feedforward and feedback schemes are analyzed. The feedback control, if proper care has been taken, exhibits better robustness and transient performance.

Wen, John T.↗

NASA NTRS1988

Real time thermal imaging of high temperature semiconductor melts

A real time thermal imaging system with temperature resolution better than + or - 1 C and spatial resolution of better than 0.5 mm was developed and applied to the analysis of melt surface thermal field distributions in both Czochralski and liquid encapsulated Czochralski (LEC) growth configurations. The melt is viewed in near normal incidence by a high resolution charge coupled device camera to which is attached a very narrow bandpass filter. The resulting image is digitized and processed using a pipelined pixel processor operating at an effective 40 million operations per second thus permitting real time high frequency spatial and temporal filtering of the high temperature scene. A multi-pixel averaging algorithm was developed which permits localized, low noise sensing of temperature variations at any location in the hot zone as a function of time. This signial is used to implement initial elements of a feedforward growth control scheme which is aimed at reducing disturbances to the melt caused by the batch nature of the growth process. The effect of magnetic melt stabilization on radial melt temperature distributions was measured using this technique. Problems associated with residual internal reflections and non-optimized path geometry are discussed.

Wargo, Michael J.↗

NASA NTRS1999

Active Control of Inlet Noise on the JT15D Turbofan Engine

This report presents the key results obtained by the Vibration and Acoustics Laboratories at Virginia Tech over the year from November 1997 to December 1998 on the Active Noise Control of Turbofan Engines research project funded by NASA Langley Research Center. The concept of implementing active noise control techniques with fuselage-mounted error sensors is investigated both analytically and experimentally. The analytical part of the project involves the continued development of an advanced modeling technique to provide prediction and design guidelines for application of active noise control techniques to large, realistic high bypass engines of the type on which active control methods are expected to be applied. Results from the advanced analytical model are presented that show the effectiveness of the control strategies, and the analytical results presented for fuselage error sensors show good agreement with the experimentally observed results and provide additional insight into the control phenomena. Additional analytical results are presented for active noise control used in conjunction with a wavenumber sensing technique. The experimental work is carried out on a running JT15D turbofan jet engine in a test stand at Virginia Tech. The control strategy used in these tests was the feedforward Filtered-X LMS algorithm. The control inputs were supplied by single and multiple circumferential arrays of acoustic sources equipped with neodymium iron cobalt magnets mounted upstream of the fan. The reference signal was obtained from an inlet mounted eddy current probe. The error signals were obtained from a number of pressure transducers flush-mounted in a simulated fuselage section mounted in the engine test cell. The active control methods are investigated when implemented with the control sources embedded within the acoustically absorptive material on a passively-lined inlet. The experimental results show that the combination of active control techniques with fuselage-mounted error sensors and passive control techniques is an effective means of reducing radiated noise from turbofan engines. Strategic selection of the location of the error transducers is shown to be effective for reducing the radiation towards particular directions in the farfield. An analytical model is used to predict the behavior of the control system and to guide the experimental design configurations, and the analytical results presented show good agreement with the experimentally observed results.

Smith, Jerome P.↗

NASA NTRS2002

Single-Trial Analysis of V1 Responses Suggests Two Transmission States

Sensory processing in the visual, auditory, and somatosensory systems is often studied by recording electrical activity in response to a stimulus of interest. Typically, multiple trial responses to the stimulus are averaged to isolate the stereotypic response from noise. However, averaging ignores dynamic variability in the neuronal response, which is potentially critical to understanding stimulus-processing schemes. Thus, we developed the multiple component, Event-Related Potential (mcERP) model. This model asserts that multiple components, defined as stereotypic waveforms, comprise the stimulus-evoked response and that these components may vary in amplitude and latency from trial to trial. Application of this model to data recorded simultaneously from all six laminae of V1 in an awake, behaving monkey performing a visual discrimination yielded three components. The first component localized to granular V1, the second was located in supragranular V1, and the final component displayed a multi-laminar distribution. These modeling results, which take into account single-trial response dynamics, illustrated that the initial activation of VI occurs in the granular layer followed by activation in the supragranular layers. This finding is expected because the average response in those layers demonstrates the same progression and because anatomical evidence suggests that the feedforward input in V1 enters the granular layer and progresses to supragranular layers. In addition to these findings, the granular component of the model displayed several interesting trial-to-trial characteristics including (1) a bimodal latency distribution, (2) a latency-related variation in response amplitude, (3) a latency correlation with the supragranular component, and (4) an amplitude and latency association with the multi-laminar component. Direct analyses of the single-trial data were consistent with these model predictions. These findings suggest that V1 has at least 2 transmission states, which may be modulated by various effects such as attention, dynamics in local EEG rhythm, or variation in sensory inputs.

Shah, A. S.↗