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At least 19 records

Precise synchronization of phasor measurements in electric power systems

Phasors representing positive sequence voltages and currents in a power network are in the most important parameters in several monitoring, control, and protection functions in interconnected electric power networks. Recent advances in computer relaying have led to very efficient and accurate phasor measurement systems. When the phasors to be measured are separated by hundreds of miles, it becomes necessary to synchronize the measurement processes, so that a consistent description of the state of the power system can be established. Global Positioning System (GPS) transmissions offer an ideal source for synchronization of phasor measurements. The concept and implementation of this technique are described. Several uses of synchronized phasor measurements are also described. Among these are improved state estimation algorithms, state estimator enhancements, dynamic state estimates, improved control techniques, and improved protection concepts.

Phadke, Arun G.

Experimental studies in system identification of helicopter rotor dynamics

Recent experiments investigating the system identification of helicopter rotor dynamics are described. The identification makes use of a two-pass procedure that estimates the rotor dynamic states prior to estimation of the dynamic equation parameters. Estimation of the rotor states is made possible through use of the predictive information contained in blade-mounted accelerometers combined with a specialized processing scheme utilizing these signals. Descriptions of the experimental hardware and the system identification technique are given, as well as implementation issues for using the procedure on other similarly instrumented rotor blades. Finally, comparisons with other identification techniques using the same data are presented. It is demonstrated that the approach is an attractive one for measurement of a helicopter rotor's dynamic behavior.

Mckillip, Robert, Jr.

Optimization-Based Dynamic Voltage Support of Microgrids Using Energy Storage Systems

A microgrid network is characterized by a high R/X ratio, making the voltage more sensitive to active power changes compared to bulk power systems, where the voltage is regulated primarily by reactive power. Due to its sensitivity, voltage control approaches for microgrids should also consider the active power input coupling, making it very different from conventional power systems. Additionally, as the energy costs associated with active and reactive powers are different and the operational conditions of microgrids connected to active distribution systems vary over time, the ideal controller to provide voltage support must be flexible enough to handle these technical and operational constraints. This paper proposes a model predictive control approach to provide dynamic voltage support using energy storage systems. This approach uses a simplified predictive model of the system to solve the model predictive control problem. By proper selection of model predictive control weighting parameters, the quality of service provided can be adjusted to achieve the desired performance. A simulation study in MATLAB/Simulink validates the proposed approach for the Cordova, Alaska microgrid. Results show that the performance of the voltage support can be adjusted depending on the choice of weight and constraints of the controller.

24 POWER TRANSMISSION AND DISTRIBUTION

Second-order state estimation experiments using acceleration measurements

The estimation of dynamic states for feedback control of structural systems using second-order differential equations and acceleration measurements is described. The formulation of the observer model, and the design of the observer gains is discussed in detail. It is shown the second-order observer is highly stable because the stability constraints on the observer gains are model independent. The limitation of the proposed observer is the need for 'nearly' collocated actuators and accelerometers. Experimental results using a control-structure interaction testbed are presented that show the second-order observer provided more stability than a Kalman filter estimator without decreasing closed-loop performance.

Belvin, W. K.

Optimal post-experiment estimation of poorly modeled dynamic systems

Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

Mook, D. Joseph

Identification of dynamic systems, theory and formulation

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Maine, R. E.

Flight control synthesis for flexible aircraft using Eigenspace assignment

The use of eigenspace assignment techniques to synthesize flight control systems for flexible aircraft is explored. Eigenspace assignment techniques are used to achieve a specified desired eigenspace, chosen to yield desirable system impulse residue magnitudes for selected system responses. Two of these are investigated. The first directly determines constant measurement feedback gains that will yield a close-loop system eigenspace close to a desired eigenspace. The second technique selects quadratic weighting matrices in a linear quadratic control synthesis that will asymptotically yield the close-loop achievable eigenspace. Finally, the possibility of using either of these techniques with state estimation is explored. Application of the methods to synthesize integrated flight-control and structural-mode-control laws for a large flexible aircraft is demonstrated and results discussed. Eigenspace selection criteria based on design goals are discussed, and for the study case it would appear that a desirable eigenspace can be obtained. In addition, the importance of state-space selection is noted along with problems with reduced-order measurement feedback. Since the full-state control laws may be implemented with dynamic compensation (state estimation), the use of reduced-order measurement feedback is less desirable. This is especially true since no change in the transient response from the pilot's input results if state estimation is used appropriately. The potential is also noted for high actuator bandwidth requirements if the linear quadratic synthesis approach is utilized. Even with the actuator pole location selected, a problem with unmodeled modes is noted due to high bandwidth. Some suggestions for future research include investigating how to choose an eigenspace that will achieve certain desired dynamics and stability robustness, determining how the choice of measurements effects synthesis results, and exploring how the phase relationships between desired eigenvector elements effects the synthesis results.

Davidson, J. B.

Model and simulation development for turbopump health monitoring by parameter estimation

The nonlinear equations describing the flow, pressure and temperature dynamics of the High Pressure Fuel Turbopump of the Space Shuttle Main Engine are summarized and implemented in a digital simulation. Some closed form approximations to the operating curves of the turbopump are made so that closed form derivatives exist. These equations and approximations are then used to develop an extended Kalman filter that estimates the dynamic states of the turbopump and a parameter that can reflect turbopump degradation. The filter is implemented as a digital computer program and applied to data generated by the digital simulation of the turbopump with substantial noise added to the output signals. The results indicate that the parameter estimate converges quickly and accurately. This suggests that the parameter estimate can be used to monitor for turbopump degradations affecting its value.

Walker, Bruce K.

Experiments with the KITE attitude control simulator

Simulation experiments are conducted to test an attitude control technique for tethered satellites using the tether tension force to generate control torques by moving the tether attach point relative to the satellite center of mass. A scaled, one-dimensional, air-bearing supported laboratory simulation of the Kinetic Isolation Tether Experiment shows that the attitude of the simulator can be regulated to within 0.75 arcsec with a bandwidth of about 0.1 Hz. The control design includes a state estimator to calculate the vehicle mass center and to calculate the effect of the stepper motor dynamics on the state estimate. Results are presented from closed-loop attitude control experiments to verify the attitude control technique.

Powell, J. David

On-line, adaptive state estimator for active noise control

Dynamic characteristics of airframe structures are expected to vary as aircraft flight conditions change. Accurate knowledge of the changing dynamic characteristics is crucial to enhancing the performance of the active noise control system using feedback control. This research investigates the development of an adaptive, on-line state estimator using a neural network concept to conduct active noise control. In this research, an algorithm has been developed that can be used to estimate displacement and velocity responses at any locations on the structure from a limited number of acceleration measurements and input force information. The algorithm employs band-pass filters to extract from the measurement signal the frequency contents corresponding to a desired mode. The filtered signal is then used to train a neural network which consists of a linear neuron with three weights. The structure of the neural network is designed as simple as possible to increase the sampling frequency as much as possible. The weights obtained through neural network training are then used to construct the transfer function of a mode in z-domain and to identify modal properties of each mode. By using the identified transfer function and interpolating the mode shape obtained at sensor locations, the displacement and velocity responses are estimated with reasonable accuracy at any locations on the structure. The accuracy of the response estimates depends on the number of modes incorporated in the estimates and the number of sensors employed to conduct mode shape interpolation. Computer simulation demonstrates that the algorithm is capable of adapting to the varying dynamic characteristics of structural properties. Experimental implementation of the algorithm on a DSP (digital signal processing) board for a plate structure is underway. The algorithm is expected to reach the sampling frequency range of about 10 kHz to 20 kHz which needs to be maintained for a typical active noise control application.

Lim, Tae W.

Sequential estimation and satellite data assimilation in meteorology and oceanography

The role of dynamics in estimating the state of the atmosphere and ocean from incomplete and noisy data is discussed and the classical applications of four-dimensional data assimilation to large-scale atmospheric dynamics are presented. It is concluded that sequential updating of a forecast model with continuously incoming conventional and remote-sensing data is the most natural way of extracting the maximum amount of information from the imperfectly known dynamics, on the one hand, and the inaccurate and incomplete observations, on the other.

Ghil, M.