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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Input filter compensation for switching regulators

A novel input filter compensation scheme for a buck regulator that eliminates the interaction between the input filter output impedance and the regulator control loop is presented. The scheme is implemented using a feedforward loop that senses the input filter state variables and uses this information to modulate the duty cycle signal. The feedforward design process presented is seen to be straightforward and the feedforward easy to implement. Extensive experimental data supported by analytical results show that significant performance improvement is achieved with the use of feedforward in the following performance categories: loop stability, audiosusceptibility, output impedance and transient response. The use of feedforward results in isolating the switching regulator from its power source thus eliminating all interaction between the regulator and equipment upstream. In addition the use of feedforward removes some of the input filter design constraints and makes the input filter design process simpler thus making it possible to optimize the input filter. The concept of feedforward compensation can also be extended to other types of switching regulators.

Kelkar, S. S.↗
NASA NTRS1992

Passivity/Lyapunov based controller design for trajectory tracking of flexible joint manipulators

A passivity and Lyapunov based approach for the control design for the trajectory tracking problem of flexible joint robots is presented. The basic structure of the proposed controller is the sum of a model-based feedforward and a model-independent feedback. Feedforward selection and solution is analyzed for a general model for flexible joints, and for more specific and practical model structures. Passivity theory is used to design a motor state-based controller in order to input-output stabilize the error system formed by the feedforward. Observability conditions for asymptotic stability are stated and verified. In order to accommodate for modeling uncertainties and to allow for the implementation of a simplified feedforward compensation, the stability of the system is analyzed in presence of approximations in the feedforward by using a Lyapunov based robustness analysis. It is shown that under certain conditions, e.g., the desired trajectory is varying slowly enough, stability is maintained for various approximations of a canonical feedforward.

Sicard, Pierre↗
NASA NTRS1987

An approach to multivariable control of manipulators

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

Seraji, H.↗
NASA NTRS1989

Robust high-performance control for robotic manipulators

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies were merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal componet that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nomical feedforward signal.

Seraji, Homayoun↗
NASA NTRS1991

Robust high-performance control for robotic manipulators

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies have been merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal component that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and a feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nominal feedforward signal.

Seraji, Homayoun↗
NASA NTRS1982

Input filter compensation for switching regulators

The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.

Lee, F. C.↗
NASA NTRS1984

Input filter compensation for switching regulators

Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.

Lee, F. C.↗
NASA NTRS1983

Stability analysis of a buck regulator employing input filter compensation

The interaction between the input filter and the regulator often causes serious degradation of performance. The reduction in loop gain due to input filter interaction can result in system instability. An exact stability analysis of the buck regulator system is presented. The input filter parameter values are varied and system instability is predicted for the case without feedforward. The eigenvalues of the system can be brought back into the unit circle and the system thus stabilized with the addition of the feedforward loop. Measurements made for the cases with and without feedforward confirm the analytical prediction.

Kelkar, S. S.↗
NASA NTRS1991

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Ross, Muriel D.↗
NASA NTRS1991

Model reference adaptive control of flexible robots in the presence of sudden load changes

Direct command generator tracker based model reference adaptive control (MRAC) algorithms are applied to the dynamics for a flexible-joint arm in the presence of sudden load changes. Because of the need to satisfy a positive real condition, such MRAC procedures are designed so that a feedforward augmented output follows the reference model output, thus, resulting in an ultimately bounded rather than zero output error. Thus, modifications are suggested and tested that: (1) incorporate feedforward into the reference model's output as well as the plant's output, and (2) incorporate a derivative term into only the process feedforward loop. The results of these simulations give a response with zero steady state model following error, and thus encourage further use of MRAC for more complex flexibile robotic systems.

Steinvorth, Rodrigo↗
NASA NTRS1993

Slewing maneuvers and vibration control of space structures by feedforward/feedback moment-gyro controls

This paper presents a moment-gyro control approach to the maneuver and vibration suppression of a flexible truss arm undergoing a constant slewing motion. The overall slewing motion is triggered by a feedforward input, and a companion feedback controller is employed to augment the feedforward input and subsequently to control vibrations. The feedforward input for the given motion requirement is determined from the combined CMG (Control Momentum Gyro) devices and the desired rigid-body motion. The rigid-body dynamic model has enabled us to identify the attendant CMG momentum saturation constraints. The task for vibration control is carried out in two stages; first in the search of a suitable CMG placement along the beam span for various slewing maneuvers, and subsequently in the development of Liapunov-based control algorithms for CMG spin-stabilization. Both analytical and numerical results are presented to show the effectiveness of the present approach.

Yang, Li-Farn↗
NASA NTRS1990

Neural net diagnostics for VLSI test

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.

Lin, T.↗
NASA NTRS1998

Study of a Simulation Tool to Determine Achievable Control Dynamics and Control Power Requirements with Perfect Tracking

This paper contains a study of two methods for use in a generic nonlinear simulation tool that could be used to determine achievable control dynamics and control power requirements while performing perfect tracking maneuvers over the entire flight envelope. The two methods are NDI (nonlinear dynamic inversion) and the SOFFT(Stochastic Optimal Feedforward and Feedback Technology) feedforward control structure. Equivalent discrete and continuous SOFFT feedforward controllers have been developed. These equivalent forms clearly show that the closed-loop plant model loop is a plant inversion and is the same as the NDI formulation. The main difference is that the NDI formulation has a closed-loop controller structure whereas SOFFT uses an open-loop command model. Continuous, discrete, and hybrid controller structures have been developed and integrated into the formulation. Linear simulation results show that seven different configurations all give essentially the same response, with the NDI hybrid being slightly different. The SOFFT controller gave better tracking performance compared to the NDI controller when a nonlinear saturation element was added. Future plans include evaluation using a nonlinear simulation.

Ostroff, Aaron J.↗
NASA NTRS1996

Neurofilament protein is differentially distributed in subpopulations of corticocortical projection neurons in the macaque monkey visual pathways

Previous studies of the primate cerebral cortex have shown that neurofilament protein is present in pyramidal neuron subpopulations displaying specific regional and laminar distribution patterns. In order to characterize further the neurochemical phenotype of the neurons furnishing feedforward and feedback pathways in the visual cortex of the macaque monkey, we performed an analysis of the distribution of neurofilament protein in corticocortical projection neurons in areas V1, V2, V3, V3A, V4, and MT. Injections of the retrogradely transported dyes Fast Blue and Diamidino Yellow were placed within areas V4 and MT, or in areas V1 and V2, in 14 adult rhesus monkeys, and the brains of these animals were processed for immunohistochemistry with an antibody to nonphosphorylated epitopes of the medium and heavy molecular weight subunits of the neurofilament protein. Overall, there was a higher proportion of neurons projecting from areas V1, V2, V3, and V3A to area MT that were neurofilament protein-immunoreactive (57-100%), than to area V4 (25-36%). In contrast, feedback projections from areas MT, V4, and V3 exhibited a more consistent proportion of neurofilament protein-containing neurons (70-80%), regardless of their target areas (V1 or V2). In addition, the vast majority of feedback neurons projecting to areas V1 and V2 were located in layers V and VI in areas V4 and MT, while they were observed in both supragranular and infragranular layers in area V3. The laminar distribution of feedforward projecting neurons was heterogeneous. In area V1, Meynert and layer IVB cells were found to project to area MT, while neurons projecting to area V4 were particularly dense in layer III within the foveal representation. In area V2, almost all neurons projecting to areas MT or V4 were located in layer III, whereas they were found in both layers II-III and V-VI in areas V3 and V3A. These results suggest that neurofilament protein identifies particular subpopulations of corticocortically projecting neurons with distinct regional and laminar distribution in the monkey visual system. It is possible that the preferential distribution of neurofilament protein within feedforward connections to area MT and all feedback projections is related to other distinctive properties of these corticocortical projection neurons.

Non-NASA Center↗
NASA NTRS1989

Method and apparatus for adaptive force and position control of manipulators

The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.

Seraji, Homayoun↗
NASA NTRS1976

A velocity-command controller for a VTOL aircraft

A technique is presented for calculating feedback and feedforward gain matrices that enable a VTOL aircraft to track input commands of forward and vertical velocity while maintaining acceptable responses to pilot inputs. Leverrier's algorithm is used for determining a set of state-variable, feedback gains that force the closed-loop poles and zeros of one pilot-input transfer function to pre-selected positions in the s-plane. This set of feedback gains is then used to calculate the feedback and feedforward gains for the velocity-command controller. The method is computationally attractive since the gains are determined by solving systems of linear, simultaneous equations. The method is used in a digital simulation of the CH-47 helicopter to control longitudinal dynamics.

Reid, G. F.↗
NASA NTRS1976

Digital adaptive control of a VTOL aircraft

A technique has been developed for calculating feedback and feedforward gain matrices that stabilize a VTOL aircraft while enabling it to track input commands of forward and vertical velocity. Leverrier's algorithm is used in a procedure for determining a set of state variable, feedback gains that force the closed loop poles and zeroes of one pilot input transfer function to be at preselected positions in the s plane. This set of feedback gains is then used to calculate the feedback and feedforward gains for the velocity command controller. The method is computationally attractive since the gains are determined by solving systems of linear, simultaneous equations. Responses obtained using a digital simulation of the longitudinal dynamics of the CH-47 helicopter are presented.

Reid, G. F.↗
NASA NTRS1976

A velocity-command controller for a VTOL aircraft

A technique is presented for calculating feedback and feedforward gain matrices that enable a VTOL aircraft to track input commands of forward and vertical velocity while maintaining acceptable responses to pilot inputs. Leverrier's algorithm is used for determining a set of state-variable, feedback gains that force the closed-loop poles and zeros of one pilot-input transfer function to pre-selected positions in the s-plane. This set of feedback gains is then used to calculate the feedback and feedforward gains for the velocity-command controller. The method is computationally attractive since the gains are determined by solving systems of linear, simultaneous equations. The method has been used in a digital simulation of the CH-47 helicopter to control longitudinal dynamics.

Reid, G. F.↗