Distributed energy management systems (EMS) open up a host of alternative design options. Simulation plays an important role in evaluating performance and in comparing alternative designs. Currently all the proposed d...
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Distributed energy management systems (EMS) open up a host of alternative design options. Simulation plays an important role in evaluating performance and in comparing alternative designs. Currently all the proposed distributed EMSs are local area network (LAN)-based. A LAN simulator, LANSIM, has been developed. To illustrate the application of LANSIM, comparisons are made with different distributed EMS configurations, different LAN technologies (Ethernet and FDDI), and different Ethernet implementations.< >
This paper presents an instability version of an earlier result by Tsypkin and Polyak (1991) on robust stability analysis using a modified Nyquist plot. The result is shown to be useful for presenting robust stability...
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This paper presents an instability version of an earlier result by Tsypkin and Polyak (1991) on robust stability analysis using a modified Nyquist plot. The result is shown to be useful for presenting robust stability and instability margins for feedback systems.
The Joint Detection/Estimation Filter (JDEF) [1,2] can be utilized to improve the performance of a single Extended Kalmart Filter (EKF) when the problem of estimation involves a large initial variance. In this case th...
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The Joint Detection/Estimation Filter (JDEF) [1,2] can be utilized to improve the performance of a single Extended Kalmart Filter (EKF) when the problem of estimation involves a large initial variance. In this case the JDEF is used to estimate the presence and location of a point target when the received signal is corrupted by multipath. In the formulation of the problem it was assumed that both the target and sensor were stationary and that there was an equal probability of the point target being present or absent along a center look direction. This implementation of the JDEF proved to be quite successful and can be easily expanded to estimate a larger number of unknown parameters.
This paper addresses the problem of multi sensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusi...
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This paper addresses the problem of multi sensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusion approach offers the potential for increased target resolution in range/azimuth space. The technique employs joint detection/estimation filters (JDEF) for target detection and parameter localization. The JDEF approach segments the aggregate nonlinear model over the entire target resolution space into subcells. This partitioning leads to extremely accurtate detection and parameter estimation. The proposed JDEF approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, noncentralized, and distributed data fusion.
In this paper high order vector filter equations are developed for estimation in non-Gaussian noise. The difference between the filters developed here and the standard Kalman filter is that the filter equation contain...
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In this paper high order vector filter equations are developed for estimation in non-Gaussian noise. The difference between the filters developed here and the standard Kalman filter is that the filter equation contains nonlinear functions of the innovations process. These filters are general in that the initial state covariance, the measurement noise covariance, and the process noise covariance can all have non-Gaussian distributions. Two filter structures are developed. The first filter is designed for systems with asymmetric probability densities. The second is designed for systems with symmetric probability densities. Experimental evaluation of these filters for estimation in non-Gaussian noise, formed from Gaussian sum distributions, shows that these filters perform much better than the standard Kalman filter, and close to the optimal Bayesian estimator.
This paper addresses the problem of multisensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusio...
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This paper addresses the problem of multisensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusion approach offers the potential for increased target resolution in range/azimuth space. The technique employs joint detection/estimation (JDE) filters for target detection and target parameter localization. The JDE approach segments the aggregate nonlinear model over the entire target resolution space into resolution subcells. This partitioning leads to extremely accurtate detection and parameter estimation. The proposed JDE approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, noncentralized, and distributed data fusion.
The problem of model order selection in the presence of parametric uncertainty is considered. A high resolution joint detection/estimation filter is used to detect the correct order of the model and estimate the signa...
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The problem of model order selection in the presence of parametric uncertainty is considered. A high resolution joint detection/estimation filter is used to detect the correct order of the model and estimate the signal parameters. Simulations indicate the excellent performance of the method.
control methods based on using the relative motion between the manipulator and the workpiece are described for controlling the force of a one-dimensional manipulator, in which it is assumed that there are no collision...
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control methods based on using the relative motion between the manipulator and the workpiece are described for controlling the force of a one-dimensional manipulator, in which it is assumed that there are no collisions between the manipulator and the workpiece and we use a computed force law which is similar to the computed torque law in the trajectory tracking problem of a manipulator. We consider two cases depending on whether the position and velocity of the workpiece (or end-effector) are available or not to calculate the computed force control. The effectiveness of the proposed control methods is illustrated by some computer simulations.
Apparent reflectivity factors measured by a radar operating at an attenuating wavelength can be adequately predicted by using the reflectivity factors at horizontal and vertical polarizations measured at a non-attenua...
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Apparent reflectivity factors measured by a radar operating at an attenuating wavelength can be adequately predicted by using the reflectivity factors at horizontal and vertical polarizations measured at a non-attenuating wavelength. This capability is important for understanding effects of rainfall on both microwave communication systems and the operation of weather radars operating at attenuating wavelengths. This paper examines and tests this capability by using S-band dual polarization radar measurements to predict C-band radar reflectivity measurements of the same storm but from a different location. The predictions of C-band observations were obtained from disdrometer-derived relationships between S-band reflectivity factor Z/sub H/(10 cm) and differential reflectivity Z/sub DR/ measurements and C-band reflectivity factor Z/sub H/(5 cm) and specific attenuation A/sub H/. Apparent reflectivity factor measurements at C-band, derived from S-band measurements, compared very well with actual measurements in the same storm. The results support the use of the dual polarization radar technique for predicting scattering and attenuation effects of narrow beam microwave signals propagating through rain-filled media along paths other than that traversed by the radar.< >
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