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In a smart grid, electricity energy demands requested from down-stream sectors continuously increase. One way to meet the energy demands is utilizing a Non-Intrusive Load Monitoring (NILM)-style system to monitor and manage residential and commercial electrical appliances in respond to demand response programs. NILM is as an electricity energy audit to energy-saving issues.This paper aims at developing an NILM identification considering the influence of voltage variations. An NILM system normally consists of "Data Acquisition", "Event Detection and Feature Extraction", and "Load Classification." The goal of load classification in NILM is to identify the operation ON/OFF status of individual household appliances. The k-Nearest Neighbors Classifier is used as the load classifier of the NILM. In NILM, measured physical phenomena, voltage signals/power profiles, to load classification for long-term load monitoring vary. The variations affect the identification performance. In this paper, a cross-validation strategy is conducted and used to deal with sampled data with systematic errors from classified loads. Different types of loads are used to verify the influence of the voltage variations to load identifications. As the experimentation reported in this paper shows, a satisfactory recognition rate of 97.60% to the NILM load identification addressed in this paper is achieved. The proposed NILM system is able to classify loads with proper robustness.

As a basic structure of computational geometry, Voronoi Diagram is important to data analysis of GIS. Considering the limitations of traditional vectorial and raster generation algorithm of Voronoi diagram, this paper proposes a spherical Full-Feature Voronoi diagram generation algorithm based on vector data. Through the design of an integrated perspective projection model, data and its connected relationship on the surface of a sphere will be projected to the Euclidean plane. And the discrete feature sets on this Euclidean plane will become point sets for generating sub-Voronoi diagrams. Then these sub-Voronoi diagrams will be merged if they belong to the same feature to accomplish the generation of spherical full-feature Voronoi Diagram. The result of empirical experiment shows that this algorithm is viable, and the accuracy of this algorithm has been discussed at the end of the paper.

In order to improve the accuracy of electro-optical tracking system, a novel feed forward-IMC controller based on Internal Model Control has been designed and made the simulation on the system. The simulation result showed that the feed forward-IMC controller can meet the need of high accuracy of electro-optical tracking system and it also have good feasibility and robustness. It has the better tracking performance in comparison with other high accuracy controller. It is able to converge efficiently and tracking accuracy can be increased several times.

Due to the problems of target motion parameter can not be directly predict and predicting accuracy reduced caused by miss distance in TV tracking system,an uncertain factor γ was introduced in the measurement equation, and it's probability to represent the system delay volume. At the same time according to the theory of Unscented Kalman filtering,the calculation algorithm of state estimation in nonlinear system with measurement delay is given(called measurement delay Unscented Kalman filter). And then,it is applied in equivalent compound control of TV tracking system. The simulation results show that introduction uncertain factor in measurement equation for describing measurement delay is valid, and can greatly reduced predicting error and tracking.

Electro-optical tracking devices in the television or infrared automatic tracking system, miss distance lag system overshoot increased, lengthened the transitional period, affecting the stability control system and reduce the tracking precision.Feedforward control technology is to improve the tracking accuracy and to maintain the stability of the system an effective way. The speed of introduction of the forecast information as feedforward control signals constitute the equivalent composite control can be approximated to achieve feedforward control technology. The filter for the synthesis of the target location information with lag, interference is the key problem of compound control technology. In order to obtain the high-precision forecasting velocity of moving target, Kalman filter with the measurement lag is designed. Forecasting velocity of moving target can obtain by forecasting the synthesis target position with measurement lag. The actual Electro-optical tracking equivalent compound control system simulation and experimental results show that the velocity of moving target can be forecasted by using the methods and tracking precision can be improved in servo-control system.