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This paper deals with the problem of identifying the mathematical model of a dry-clutch transmission system, from input-output data experimentally collected on a real vehicle. The proposed identification procedure is based on a set-membership identification approach, where a-priori information on the structure of the physical model are taken into account in the selection of the model class. Parameter...
The tremendous usage of power electronic devices in power system makes the harmonic pollution can't be ignored any more. Harmonic contents in power system is one of the indexes to evaluate the power quality. Alternative Transients Program (ATP) has obvious advantages in transient calculation. While it is difficult to carry out the electromagnetic transient calculation of actual power grid due to its...
It is conceivable that the future fleet of US Navy vessels will deploy multiple high power AC and DC loads that must be reliably energized. Integration and operation of AC and DC loads will likely be achieved using an intelligently controlled microgrid architecture that is able to actively regulate and distribute power from both AC generation sources and DC energy storage devices. Some future loads...
In this paper we propose an autotuning method that combines a setup for decentralized relay autotuning of two-input two-output systems with an identification method that uses short experiments to estimate up to second-order time-delayed systems. A small modification of the experiment gives better low-frequency excitation and improved models. The method is successfully demonstrated in simulations and...
This study suggests an ELM (Extreme Learning Machine) model that is based on a TSK (Takagi-Sugeno-Kang) fuzzy model and compares its performance projection with the existing ELM model. The TSK based ELM model replaces the in the existing model with a linear function. Additionally, the center of the cluster is haphazardly set. The Weighted value between the hidden layer and input is nonexistent whereas...
Power quality disturbances carry a large amount of information reflecting the operating conditions of the system and equipment, providing a data source for load modeling. Avoiding high complexity of computation in sampling side and waste of hardware, the compressed sensing (CS) theory is applied to processing the power quality monitoring signal. On the basis of the disturbance data processed by compressed...
The present paper is part of a larger project which aims to monitor and mitigate dust on the PV systems in the city of Arequipa. Its objective is to present a simplified model for simulating PV panels for the design and project maximum power point tracker - MPPT controllers. With an experimental setup, signals of voltage, current, power, irradiance and temperature were acquired. A SEPIC converter...
The promising benefits of the renewable sources based on distributed generation are pushing the future energy markets to invest more into the available renewable systems. This research will focus on integrating available renewable energy resources in Kingdom of Saudi Arabia in the electric grid to minimize the energy production from fossil fuels through continuous prediction and forecast of demand...
Traditionally, load forecasting tools include weather variables as model inputs. Northern Ireland has seen a major increase in weather dependent, renewable generation over the last number of years creating a double impact by weather parameters in the load profile. The new generation is not visible to, or controllable by, the system operator and is presenting major challenges to traditional load forecasting...
Modeling low voltage consumption and generation individually is becoming an essential task for DSOs to plan infrastructure investments more efficiently and manage the network more actively in the effort of making grids smarter. In this paper, three different approaches for modeling such individuals is exposed. A quasi-sequential approach which holds the exact distributions of consumption and generation...
Small-scale, renewable generation which is embedded in the distribution network is causing previously unseen fluctuations in demand. In Northern Ireland this new generation, which is not visible to, or controllable by, the system operator, is presenting major challenges for accurate load forecasting. Currently deployed load forecasting methods are struggling to cope due to the rapid growth in this...
Aspirations of grid independence could be achieved by residential power systems connected only to small highly variable loads if overall demand on the network can be accurately anticipated. Absence of the diversity found on networks with larger load cohorts or consistent industrial customers makes such overall load profiles difficult to anticipate on even a short term basis. Here, existing forecasting...
In the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training...
SRAM-based FPGA has become a core device in space application. However, based on CMOS technology, SRAM-based FPGA is sensitive for SEU effect. JTAG circuit is a significant module of SRAM-based FPGA, executing boundary-scan test and global configuration function. SEU effect can result in function disturbance of JTAG circuit. To adopt reasonable harden strategies for JTAG circuit, the paper puts forward...
The visual simulation system which the docking process of replenishment at sea is constructed based on MultiGen Creator and Vega Prime. In a bid to modeling and driving of the visual simulation, a large number of the real-time data should be transformed for simulation in which the entire process of replenishment at sea. According to the complicated power and movement state of the docking mechanism...
Following the Service-Oriented Architecture, a large number of diversified Cloud services are exposed as Web APIs (Application Program Interface), which serve as the contracts between the service providers and service consumers. Due to their massive and broad applications, any flaw in the cloud APIs may lead to serious consequences. API testing is thus necessary to ensure the availability, reliability,...
In order to realize the optimal control of variable frequency circulating pumps for ground source heat pump (GSHP) system it is necessary to build the prediction model of the total power consumption of GSHP system based on running data. Firstly the power consumption analysis of GSHP system with bilateral variable flow is presented. Then a Hyberball Cerebellar Model Articulation Controller (HCMAC)...
In this paper we introduce a model of lifelong learning, based on a Network of Experts. New tasks / experts are learned and added to the model sequentially, building on what was learned before. To ensure scalability of this process, data from previous tasks cannot be stored and hence is not available when learning a new task. A critical issue in such context, not addressed in the literature so far,...
Shape models provide a compact parameterization of a class of shapes, and have been shown to be important to a variety of vision problems, including object detection, tracking, and image segmentation. Learning generative shape models from grid-structured representations, aka silhouettes, is usually hindered by (1) data likelihoods with intractable marginals and posteriors, (2) high-dimensional shape...
In order to establish a simple mathematical model with high accuracy for the new built YUPENG ship of Dalian Maritime University, this paper adopts the modeling method to establish a nonlinear response mathematical model for YUPENG ship. The turning and the zig-zag tests simulation experiments are carried out on this model, the conformity of simulation overall is about 94.5% in this experiment. Base...
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